Unnamed: 0 int64 0 41k | title stringlengths 4 274 | category stringlengths 5 18 | summary stringlengths 22 3.66k | theme stringclasses 8
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14,902 | FASTSUBS: An Efficient and Exact Procedure for Finding the Most Likely
Lexical Substitutes Based on an N-gram Language Model | cs.CL | Lexical substitutes have found use in areas such as paraphrasing, text
simplification, machine translation, word sense disambiguation, and part of
speech induction. However the computational complexity of accurately
identifying the most likely substitutes for a word has made large scale
experiments difficult. In this p... | computer science |
14,903 | Système d'aide à l'accès lexical : trouver le mot qu'on a sur le
bout de la langue | cs.CL | The study of the Tip of the Tongue phenomenon (TOT) provides valuable clues
and insights concerning the organisation of the mental lexicon (meaning, number
of syllables, relation with other words, etc.). This paper describes a tool
based on psycho-linguistic observations concerning the TOT phenomenon. We've
built it to... | computer science |
14,904 | Adversarial Evaluation for Models of Natural Language | cs.CL | We now have a rich and growing set of modeling tools and algorithms for
inducing linguistic structure from text that is less than fully annotated. In
this paper, we discuss some of the weaknesses of our current methodology. We
present a new abstract framework for evaluating natural language processing
(NLP) models in g... | computer science |
14,905 | Learning to Map Sentences to Logical Form: Structured Classification
with Probabilistic Categorial Grammars | cs.CL | This paper addresses the problem of mapping natural language sentences to
lambda-calculus encodings of their meaning. We describe a learning algorithm
that takes as input a training set of sentences labeled with expressions in the
lambda calculus. The algorithm induces a grammar for the problem, along with a
log-linear... | computer science |
14,906 | Clustering based approach extracting collocations | cs.CL | The following study presents a collocation extraction approach based on
clustering technique. This study uses a combination of several classical
measures which cover all aspects of a given corpus then it suggests separating
bigrams found in the corpus in several disjoint groups according to the
probability of presence ... | computer science |
14,907 | Automatic Segmentation of Manipuri (Meiteilon) Word into Syllabic Units | cs.CL | The work of automatic segmentation of a Manipuri language (or Meiteilon) word
into syllabic units is demonstrated in this paper. This language is a scheduled
Indian language of Tibeto-Burman origin, which is also a very highly
agglutinative language. This language usages two script: a Bengali script and
Meitei Mayek (S... | computer science |
14,908 | Appropriate Nouns with Obligatory Modifiers | cs.CL | The notion of appropriate sequence as introduced by Z. Harris provides a
powerful syntactic way of analysing the detailed meaning of various sentences,
including ambiguous ones. In an adjectival sentence like 'The leather was
yellow', the introduction of an appropriate noun, here 'colour', specifies
which quality the a... | computer science |
14,909 | A prototype for projecting HPSG syntactic lexica towards LMF | cs.CL | The comparative evaluation of Arabic HPSG grammar lexica requires a deep
study of their linguistic coverage. The complexity of this task results mainly
from the heterogeneity of the descriptive components within those lexica
(underlying linguistic resources and different data categories, for example).
It is therefore e... | computer science |
14,910 | Statistical sentiment analysis performance in Opinum | cs.CL | The classification of opinion texts in positive and negative is becoming a
subject of great interest in sentiment analysis. The existence of many labeled
opinions motivates the use of statistical and machine-learning methods.
First-order statistics have proven to be very limited in this field. The Opinum
approach is ba... | computer science |
14,911 | Towards the Fully Automatic Merging of Lexical Resources: A Step Forward | cs.CL | This article reports on the results of the research done towards the fully
automatically merging of lexical resources. Our main goal is to show the
generality of the proposed approach, which have been previously applied to
merge Spanish Subcategorization Frames lexica. In this work we extend and apply
the same techniqu... | computer science |
14,912 | Automatic lexical semantic classification of nouns | cs.CL | The work we present here addresses cue-based noun classification in English
and Spanish. Its main objective is to automatically acquire lexical semantic
information by classifying nouns into previously known noun lexical classes.
This is achieved by using particular aspects of linguistic contexts as cues
that identify ... | computer science |
14,913 | A Classification of Adjectives for Polarity Lexicons Enhancement | cs.CL | Subjective language detection is one of the most important challenges in
Sentiment Analysis. Because of the weight and frequency in opinionated texts,
adjectives are considered a key piece in the opinion extraction process. These
subjective units are more and more frequently collected in polarity lexicons in
which they... | computer science |
14,914 | Mining and Exploiting Domain-Specific Corpora in the PANACEA Platform | cs.CL | The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform
that automates the stages involved in the acquisition, production, updating and
maintenance of the large language resources required by, among others, MT
systems. The development of a Corpus Acquisition Component (CAC) for extracting
monolingua... | computer science |
14,915 | Automatic Detection of Non-deverbal Event Nouns for Quick Lexicon
Production | cs.CL | In this work we present the results of our experimental work on the
develop-ment of lexical class-based lexica by automatic means. The objective is
to as-sess the use of linguistic lexical-class based information as a feature
selection methodology for the use of classifiers in quick lexical development.
The results sho... | computer science |
14,916 | Using qualia information to identify lexical semantic classes in an
unsupervised clustering task | cs.CL | Acquiring lexical information is a complex problem, typically approached by
relying on a number of contexts to contribute information for classification.
One of the first issues to address in this domain is the determination of such
contexts. The work presented here proposes the use of automatically obtained
FORMAL rol... | computer science |
14,917 | Probabilistic Topic and Syntax Modeling with Part-of-Speech LDA | cs.CL | This article presents a probabilistic generative model for text based on
semantic topics and syntactic classes called Part-of-Speech LDA (POSLDA).
POSLDA simultaneously uncovers short-range syntactic patterns (syntax) and
long-range semantic patterns (topics) that exist in document collections. This
results in word dis... | computer science |
14,918 | SYNTAGMA. A Linguistic Approach to Parsing | cs.CL | SYNTAGMA is a rule-based parsing system, structured on two levels: a general
parsing engine and a language specific grammar. The parsing engine is a
language independent program, while grammar and language specific rules and
resources are given as text files, consisting in a list of constituent
structuresand a lexical ... | computer science |
14,919 | Advances in the Logical Representation of Lexical Semantics | cs.CL | The integration of lexical semantics and pragmatics in the analysis of the
meaning of natural lan- guage has prompted changes to the global framework
derived from Montague. In those works, the original lexicon, in which words
were assigned an atomic type of a single-sorted logic, has been re- placed by a
set of many-fa... | computer science |
14,920 | Learning to answer questions | cs.CL | We present an open-domain Question-Answering system that learns to answer
questions based on successful past interactions. We follow a pattern-based
approach to Answer-Extraction, where (lexico-syntactic) patterns that relate a
question to its answer are automatically learned and used to answer future
questions. Result... | computer science |
14,921 | Analysing Quality of English-Hindi Machine Translation Engine Outputs
Using Bayesian Classification | cs.CL | This paper considers the problem for estimating the quality of machine
translation outputs which are independent of human intervention and are
generally addressed using machine learning techniques.There are various
measures through which a machine learns translations quality. Automatic
Evaluation metrics produce good c... | computer science |
14,922 | Preparing Korean Data for the Shared Task on Parsing Morphologically
Rich Languages | cs.CL | This document gives a brief description of Korean data prepared for the SPMRL
2013 shared task. A total of 27,363 sentences with 350,090 tokens are used for
the shared task. All constituent trees are collected from the KAIST Treebank
and transformed to the Penn Treebank style. All dependency trees are converted
from th... | computer science |
14,923 | Implementation of nlization framework for verbs, pronouns and
determiners with eugene | cs.CL | UNL system is designed and implemented by a nonprofit organization, UNDL
Foundation at Geneva in 1999. UNL applications are application softwares that
allow end users to accomplish natural language tasks, such as translating,
summarizing, retrieving or extracting information, etc. Two major web based
application softwa... | computer science |
14,924 | General Purpose Textual Sentiment Analysis and Emotion Detection Tools | cs.CL | Textual sentiment analysis and emotion detection consists in retrieving the
sentiment or emotion carried by a text or document. This task can be useful in
many domains: opinion mining, prediction, feedbacks, etc. However, building a
general purpose tool for doing sentiment analysis and emotion detection raises
a number... | computer science |
14,925 | Exploiting Similarities among Languages for Machine Translation | cs.CL | Dictionaries and phrase tables are the basis of modern statistical machine
translation systems. This paper develops a method that can automate the process
of generating and extending dictionaries and phrase tables. Our method can
translate missing word and phrase entries by learning language structures based
on large m... | computer science |
14,926 | Text segmentation with character-level text embeddings | cs.CL | Learning word representations has recently seen much success in computational
linguistics. However, assuming sequences of word tokens as input to linguistic
analysis is often unjustified. For many languages word segmentation is a
non-trivial task and naturally occurring text is sometimes a mixture of natural
language s... | computer science |
14,927 | JRC EuroVoc Indexer JEX - A freely available multi-label categorisation
tool | cs.CL | EuroVoc (2012) is a highly multilingual thesaurus consisting of over 6,700
hierarchically organised subject domains used by European Institutions and many
authorities in Member States of the European Union (EU) for the classification
and retrieval of official documents. JEX is JRC-developed multi-label
classification s... | computer science |
14,928 | DGT-TM: A freely Available Translation Memory in 22 Languages | cs.CL | The European Commission's (EC) Directorate General for Translation, together
with the EC's Joint Research Centre, is making available a large translation
memory (TM; i.e. sentences and their professionally produced translations)
covering twenty-two official European Union (EU) languages and their 231
language pairs. Su... | computer science |
14,929 | An introduction to the Europe Media Monitor family of applications | cs.CL | Most large organizations have dedicated departments that monitor the media to
keep up-to-date with relevant developments and to keep an eye on how they are
represented in the news. Part of this media monitoring work can be automated.
In the European Union with its 23 official languages, it is particularly
important to ... | computer science |
14,930 | Even the Abstract have Colour: Consensus in Word-Colour Associations | cs.CL | Colour is a key component in the successful dissemination of information.
Since many real-world concepts are associated with colour, for example danger
with red, linguistic information is often complemented with the use of
appropriate colours in information visualization and product marketing. Yet,
there is no comprehe... | computer science |
14,931 | LDC Arabic Treebanks and Associated Corpora: Data Divisions Manual | cs.CL | The Linguistic Data Consortium (LDC) has developed hundreds of data corpora
for natural language processing (NLP) research. Among these are a number of
annotated treebank corpora for Arabic. Typically, these corpora consist of a
single collection of annotated documents. NLP research, however, usually
requires multiple ... | computer science |
14,932 | A Hybrid Algorithm for Matching Arabic Names | cs.CL | In this paper, a new hybrid algorithm which combines both of token-based and
character-based approaches is presented. The basic Levenshtein approach has
been extended to token-based distance metric. The distance metric is enhanced
to set the proper granularity level behavior of the algorithm. It smoothly maps
a thresho... | computer science |
14,933 | Sentiment Analysis: How to Derive Prior Polarities from SentiWordNet | cs.CL | Assigning a positive or negative score to a word out of context (i.e. a
word's prior polarity) is a challenging task for sentiment analysis. In the
literature, various approaches based on SentiWordNet have been proposed. In
this paper, we compare the most often used techniques together with newly
proposed ones and inco... | computer science |
14,934 | From Once Upon a Time to Happily Ever After: Tracking Emotions in Novels
and Fairy Tales | cs.CL | Today we have access to unprecedented amounts of literary texts. However,
search still relies heavily on key words. In this paper, we show how sentiment
analysis can be used in tandem with effective visualizations to quantify and
track emotions in both individual books and across very large collections. We
introduce th... | computer science |
14,935 | Colourful Language: Measuring Word-Colour Associations | cs.CL | Since many real-world concepts are associated with colour, for example danger
with red, linguistic information is often complimented with the use of
appropriate colours in information visualization and product marketing. Yet,
there is no comprehensive resource that captures concept-colour associations.
We present a met... | computer science |
14,936 | JRC-Names: A freely available, highly multilingual named entity resource | cs.CL | This paper describes a new, freely available, highly multilingual named
entity resource for person and organisation names that has been compiled over
seven years of large-scale multilingual news analysis combined with Wikipedia
mining, resulting in 205,000 per-son and organisation names plus about the same
number of sp... | computer science |
14,937 | Acronym recognition and processing in 22 languages | cs.CL | We are presenting work on recognising acronyms of the form Long-Form
(Short-Form) such as "International Monetary Fund (IMF)" in millions of news
articles in twenty-two languages, as part of our more general effort to
recognise entities and their variants in news text and to use them for the
automatic analysis of the n... | computer science |
14,938 | Sentiment Analysis in the News | cs.CL | Recent years have brought a significant growth in the volume of research in
sentiment analysis, mostly on highly subjective text types (movie or product
reviews). The main difference these texts have with news articles is that their
target is clearly defined and unique across the text. Following different
annotation ef... | computer science |
14,939 | Tracking Sentiment in Mail: How Genders Differ on Emotional Axes | cs.CL | With the widespread use of email, we now have access to unprecedented amounts
of text that we ourselves have written. In this paper, we show how sentiment
analysis can be used in tandem with effective visualizations to quantify and
track emotions in many types of mail. We create a large word--emotion
association lexico... | computer science |
14,940 | Using Nuances of Emotion to Identify Personality | cs.CL | Past work on personality detection has shown that frequency of lexical
categories such as first person pronouns, past tense verbs, and sentiment words
have significant correlations with personality traits. In this paper, for the
first time, we show that fine affect (emotion) categories such as that of
excitement, guilt... | computer science |
14,941 | Domain-Specific Sentiment Word Extraction by Seed Expansion and Pattern
Generation | cs.CL | This paper focuses on the automatic extraction of domain-specific sentiment
word (DSSW), which is a fundamental subtask of sentiment analysis. Most
previous work utilizes manual patterns for this task. However, the performance
of those methods highly relies on the labelled patterns or selected seeds. In
order to overco... | computer science |
14,942 | Development and Transcription of Assamese Speech Corpus | cs.CL | A balanced speech corpus is the basic need for any speech processing task. In
this report we describe our effort on development of Assamese speech corpus. We
mainly focused on some issues and challenges faced during development of the
corpus. Being a less computationally aware language, this is the first effort
to deve... | computer science |
14,943 | Embedding Semantic Relations into Word Representations | cs.CL | Learning representations for semantic relations is important for various
tasks such as analogy detection, relational search, and relation
classification. Although there have been several proposals for learning
representations for individual words, learning word representations that
explicitly capture the semantic relat... | computer science |
14,944 | Fast Rhetorical Structure Theory Discourse Parsing | cs.CL | In recent years, There has been a variety of research on discourse parsing,
particularly RST discourse parsing. Most of the recent work on RST parsing has
focused on implementing new types of features or learning algorithms in order
to improve accuracy, with relatively little focus on efficiency, robustness, or
practic... | computer science |
14,945 | Turn Segmentation into Utterances for Arabic Spontaneous Dialogues and
Instance Messages | cs.CL | Text segmentation task is an essential processing task for many of Natural
Language Processing (NLP) such as text summarization, text translation,
dialogue language understanding, among others. Turns segmentation considered
the key player in dialogue understanding task for building automatic
Human-Computer systems. In ... | computer science |
14,946 | A Survey of Arabic Dialogues Understanding for Spontaneous Dialogues and
Instant Message | cs.CL | Building dialogues systems interaction has recently gained considerable
attention, but most of the resources and systems built so far are tailored to
English and other Indo-European languages. The need for designing systems for
other languages is increasing such as Arabic language. For this reasons, there
are more inte... | computer science |
14,947 | Indonesian Social Media Sentiment Analysis With Sarcasm Detection | cs.CL | Sarcasm is considered one of the most difficult problem in sentiment
analysis. In our ob-servation on Indonesian social media, for cer-tain topics,
people tend to criticize something using sarcasm. Here, we proposed two
additional features to detect sarcasm after a common sentiment analysis is
conducted. The features a... | computer science |
14,948 | Sentiment Analysis For Modern Standard Arabic And Colloquial | cs.CL | The rise of social media such as blogs and social networks has fueled
interest in sentiment analysis. With the proliferation of reviews, ratings,
recommendations and other forms of online expression, online opinion has turned
into a kind of virtual currency for businesses looking to market their
products, identify new ... | computer science |
14,949 | Feature selection using Fisher's ratio technique for automatic speech
recognition | cs.CL | Automatic Speech Recognition involves mainly two steps; feature extraction
and classification . Mel Frequency Cepstral Coefficient is used as one of the
prominent feature extraction techniques in ASR. Usually, the set of all 12 MFCC
coefficients is used as the feature vector in the classification step. But the
question... | computer science |
14,950 | Rank diversity of languages: Generic behavior in computational
linguistics | cs.CL | Statistical studies of languages have focused on the rank-frequency
distribution of words. Instead, we introduce here a measure of how word ranks
change in time and call this distribution \emph{rank diversity}. We calculate
this diversity for books published in six European languages since 1800, and
find that it follow... | computer science |
14,951 | Arabic Inquiry-Answer Dialogue Acts Annotation Schema | cs.CL | We present an annotation schema as part of an effort to create a manually
annotated corpus for Arabic dialogue language understanding including spoken
dialogue and written "chat" dialogue for inquiry-answer domain. The proposed
schema handles mainly the request and response acts that occurs frequently in
inquiry-answer... | computer science |
14,952 | Sifting Robotic from Organic Text: A Natural Language Approach for
Detecting Automation on Twitter | cs.CL | Twitter, a popular social media outlet, has evolved into a vast source of
linguistic data, rich with opinion, sentiment, and discussion. Due to the
increasing popularity of Twitter, its perceived potential for exerting social
influence has led to the rise of a diverse community of automatons, commonly
referred to as bo... | computer science |
14,953 | CCG Parsing and Multiword Expressions | cs.CL | This thesis presents a study about the integration of information about
Multiword Expressions (MWEs) into parsing with Combinatory Categorial Grammar
(CCG). We build on previous work which has shown the benefit of adding
information about MWEs to syntactic parsing by implementing a similar pipeline
with CCG parsing. Mo... | computer science |
14,954 | Learning Better Word Embedding by Asymmetric Low-Rank Projection of
Knowledge Graph | cs.CL | Word embedding, which refers to low-dimensional dense vector representations
of natural words, has demonstrated its power in many natural language
processing tasks. However, it may suffer from the inaccurate and incomplete
information contained in the free text corpus as training data. To tackle this
challenge, there h... | computer science |
14,955 | Boosting Named Entity Recognition with Neural Character Embeddings | cs.CL | Most state-of-the-art named entity recognition (NER) systems rely on
handcrafted features and on the output of other NLP tasks such as
part-of-speech (POS) tagging and text chunking. In this work we propose a
language-independent NER system that uses automatically learned features only.
Our approach is based on the Cha... | computer science |
14,956 | Knowlege Graph Embedding by Flexible Translation | cs.CL | Knowledge graph embedding refers to projecting entities and relations in
knowledge graph into continuous vector spaces. State-of-the-art methods, such
as TransE, TransH, and TransR build embeddings by treating relation as
translation from head entity to tail entity. However, previous models can not
deal with reflexive/... | computer science |
14,957 | Translation Memory Retrieval Methods | cs.CL | Translation Memory (TM) systems are one of the most widely used translation
technologies. An important part of TM systems is the matching algorithm that
determines what translations get retrieved from the bank of available
translations to assist the human translator. Although detailed accounts of the
matching algorithm... | computer science |
14,958 | The IBM 2015 English Conversational Telephone Speech Recognition System | cs.CL | We describe the latest improvements to the IBM English conversational
telephone speech recognition system. Some of the techniques that were found
beneficial are: maxout networks with annealed dropout rates; networks with a
very large number of outputs trained on 2000 hours of data; joint modeling of
partially unfolded ... | computer science |
14,959 | Keyphrase Based Evaluation of Automatic Text Summarization | cs.CL | The development of methods to deal with the informative contents of the text
units in the matching process is a major challenge in automatic summary
evaluation systems that use fixed n-gram matching. The limitation causes
inaccurate matching between units in a peer and reference summaries. The
present study introduces ... | computer science |
14,960 | Representing Meaning with a Combination of Logical and Distributional
Models | cs.CL | NLP tasks differ in the semantic information they require, and at this time
no single se- mantic representation fulfills all requirements. Logic-based
representations characterize sentence structure, but do not capture the graded
aspect of meaning. Distributional models give graded similarity ratings for
words and phra... | computer science |
14,961 | Unsupervised Cross-Domain Word Representation Learning | cs.CL | Meaning of a word varies from one domain to another. Despite this important
domain dependence in word semantics, existing word representation learning
methods are bound to a single domain. Given a pair of
\emph{source}-\emph{target} domains, we propose an unsupervised method for
learning domain-specific word representa... | computer science |
14,962 | Overview of the NLPCC 2015 Shared Task: Chinese Word Segmentation and
POS Tagging for Micro-blog Texts | cs.CL | In this paper, we give an overview for the shared task at the 4th CCF
Conference on Natural Language Processing \& Chinese Computing (NLPCC 2015):
Chinese word segmentation and part-of-speech (POS) tagging for micro-blog
texts. Different with the popular used newswire datasets, the dataset of this
shared task consists ... | computer science |
14,963 | Supervised Fine Tuning for Word Embedding with Integrated Knowledge | cs.CL | Learning vector representation for words is an important research field which
may benefit many natural language processing tasks. Two limitations exist in
nearly all available models, which are the bias caused by the context
definition and the lack of knowledge utilization. They are difficult to tackle
because these al... | computer science |
14,964 | Modeling meaning: computational interpreting and understanding of
natural language fragments | cs.CL | In this introductory article we present the basics of an approach to
implementing computational interpreting of natural language aiming to model the
meanings of words and phrases. Unlike other approaches, we attempt to define
the meanings of text fragments in a composable and computer interpretable way.
We discuss mode... | computer science |
14,965 | Neural Attention Models for Sequence Classification: Analysis and
Application to Key Term Extraction and Dialogue Act Detection | cs.CL | Recurrent neural network architectures combining with attention mechanism, or
neural attention model, have shown promising performance recently for the tasks
including speech recognition, image caption generation, visual question
answering and machine translation. In this paper, neural attention model is
applied on two... | computer science |
14,966 | A Compositional Approach to Language Modeling | cs.CL | Traditional language models treat language as a finite state automaton on a
probability space over words. This is a very strong assumption when modeling
something inherently complex such as language. In this paper, we challenge this
by showing how the linear chain assumption inherent in previous work can be
translated ... | computer science |
14,967 | Domain Adaptation of Recurrent Neural Networks for Natural Language
Understanding | cs.CL | The goal of this paper is to use multi-task learning to efficiently scale
slot filling models for natural language understanding to handle multiple
target tasks or domains. The key to scalability is reducing the amount of
training data needed to learn a model for a new task. The proposed multi-task
model delivers bette... | computer science |
14,968 | Revisiting Summarization Evaluation for Scientific Articles | cs.CL | Evaluation of text summarization approaches have been mostly based on metrics
that measure similarities of system generated summaries with a set of human
written gold-standard summaries. The most widely used metric in summarization
evaluation has been the ROUGE family. ROUGE solely relies on lexical overlaps
between th... | computer science |
14,969 | Cross-lingual Models of Word Embeddings: An Empirical Comparison | cs.CL | Despite interest in using cross-lingual knowledge to learn word embeddings
for various tasks, a systematic comparison of the possible approaches is
lacking in the literature. We perform an extensive evaluation of four popular
approaches of inducing cross-lingual embeddings, each requiring a different
form of supervisio... | computer science |
14,970 | Online Updating of Word Representations for Part-of-Speech Tagging | cs.CL | We propose online unsupervised domain adaptation (DA), which is performed
incrementally as data comes in and is applicable when batch DA is not possible.
In a part-of-speech (POS) tagging evaluation, we find that online unsupervised
DA performs as well as batch DA. | computer science |
14,971 | Discriminative Phrase Embedding for Paraphrase Identification | cs.CL | This work, concerning paraphrase identification task, on one hand contributes
to expanding deep learning embeddings to include continuous and discontinuous
linguistic phrases. On the other hand, it comes up with a new scheme TF-KLD-KNN
to learn the discriminative weights of words and phrases specific to paraphrase
task... | computer science |
14,972 | Capturing Semantic Similarity for Entity Linking with Convolutional
Neural Networks | cs.CL | A key challenge in entity linking is making effective use of contextual
information to disambiguate mentions that might refer to different entities in
different contexts. We present a model that uses convolutional neural networks
to capture semantic correspondence between a mention's context and a proposed
target entit... | computer science |
14,973 | Multi-Field Structural Decomposition for Question Answering | cs.CL | This paper presents a precursory yet novel approach to the question answering
task using structural decomposition. Our system first generates linguistic
structures such as syntactic and semantic trees from text, decomposes them into
multiple fields, then indexes the terms in each field. For each question, it
decomposes... | computer science |
14,974 | Modeling Relational Information in Question-Answer Pairs with
Convolutional Neural Networks | cs.CL | In this paper, we propose convolutional neural networks for learning an
optimal representation of question and answer sentences. Their main aspect is
the use of relational information given by the matches between words from the
two members of the pair. The matches are encoded as embeddings with additional
parameters (d... | computer science |
14,975 | Character-Level Neural Translation for Multilingual Media Monitoring in
the SUMMA Project | cs.CL | The paper steps outside the comfort-zone of the traditional NLP tasks like
automatic speech recognition (ASR) and machine translation (MT) to addresses
two novel problems arising in the automated multilingual news monitoring:
segmentation of the TV and radio program ASR transcripts into individual
stories, and clusteri... | computer science |
14,976 | A new TAG Formalism for Tamil and Parser Analytics | cs.CL | Tree adjoining grammar (TAG) is specifically suited for morph rich and
agglutinated languages like Tamil due to its psycho linguistic features and
parse time dependency and morph resolution. Though TAG and LTAG formalisms have
been known for about 3 decades, efforts on designing TAG Syntax for Tamil have
not been entir... | computer science |
14,977 | RIGA at SemEval-2016 Task 8: Impact of Smatch Extensions and
Character-Level Neural Translation on AMR Parsing Accuracy | cs.CL | Two extensions to the AMR smatch scoring script are presented. The first
extension com-bines the smatch scoring script with the C6.0 rule-based
classifier to produce a human-readable report on the error patterns frequency
observed in the scored AMR graphs. This first extension results in 4% gain over
the state-of-art C... | computer science |
14,978 | An Ensemble Method to Produce High-Quality Word Embeddings | cs.CL | A currently successful approach to computational semantics is to represent
words as embeddings in a machine-learned vector space. We present an ensemble
method that combines embeddings produced by GloVe (Pennington et al., 2014) and
word2vec (Mikolov et al., 2013) with structured knowledge from the semantic
networks Co... | computer science |
14,979 | Neural Headline Generation with Sentence-wise Optimization | cs.CL | Recently, neural models have been proposed for headline generation by
learning to map documents to headlines with recurrent neural networks.
Nevertheless, as traditional neural network utilizes maximum likelihood
estimation for parameter optimization, it essentially constrains the expected
training objective within wor... | computer science |
14,980 | Transfer Learning for Low-Resource Neural Machine Translation | cs.CL | The encoder-decoder framework for neural machine translation (NMT) has been
shown effective in large data scenarios, but is much less effective for
low-resource languages. We present a transfer learning method that
significantly improves Bleu scores across a range of low-resource languages.
Our key idea is to first tra... | computer science |
14,981 | Fusing Audio, Textual and Visual Features for Sentiment Analysis of News
Videos | cs.CL | This paper presents a novel approach to perform sentiment analysis of news
videos, based on the fusion of audio, textual and visual clues extracted from
their contents. The proposed approach aims at contributing to the
semiodiscoursive study regarding the construction of the ethos (identity) of
this media universe, whi... | computer science |
14,982 | Method of Tibetan Person Knowledge Extraction | cs.CL | Person knowledge extraction is the foundation of the Tibetan knowledge graph
construction, which provides support for Tibetan question answering system,
information retrieval, information extraction and other researches, and
promotes national unity and social stability. This paper proposes a SVM and
template based appr... | computer science |
14,983 | Using Sentence-Level LSTM Language Models for Script Inference | cs.CL | There is a small but growing body of research on statistical scripts, models
of event sequences that allow probabilistic inference of implicit events from
documents. These systems operate on structured verb-argument events produced by
an NLP pipeline. We compare these systems with recent Recurrent Neural Net
models tha... | computer science |
14,984 | Learning Global Features for Coreference Resolution | cs.CL | There is compelling evidence that coreference prediction would benefit from
modeling global information about entity-clusters. Yet, state-of-the-art
performance can be achieved with systems treating each mention prediction
independently, which we attribute to the inherent difficulty of crafting
informative cluster-leve... | computer science |
14,985 | Shallow Parsing Pipeline for Hindi-English Code-Mixed Social Media Text | cs.CL | In this study, the problem of shallow parsing of Hindi-English code-mixed
social media text (CSMT) has been addressed. We have annotated the data,
developed a language identifier, a normalizer, a part-of-speech tagger and a
shallow parser. To the best of our knowledge, we are the first to attempt
shallow parsing on CSM... | computer science |
14,986 | Disfluency Detection using a Bidirectional LSTM | cs.CL | We introduce a new approach for disfluency detection using a Bidirectional
Long-Short Term Memory neural network (BLSTM). In addition to the word
sequence, the model takes as input pattern match features that were developed
to reduce sensitivity to vocabulary size in training, which lead to improved
performance over th... | computer science |
14,987 | Improving sentence compression by learning to predict gaze | cs.CL | We show how eye-tracking corpora can be used to improve sentence compression
models, presenting a novel multi-task learning algorithm based on multi-layer
LSTMs. We obtain performance competitive with or better than state-of-the-art
approaches. | computer science |
14,988 | Sentence-Level Grammatical Error Identification as Sequence-to-Sequence
Correction | cs.CL | We demonstrate that an attention-based encoder-decoder model can be used for
sentence-level grammatical error identification for the Automated Evaluation of
Scientific Writing (AESW) Shared Task 2016. The attention-based encoder-decoder
models can be used for the generation of corrections, in addition to error
identifi... | computer science |
14,989 | From Incremental Meaning to Semantic Unit (phrase by phrase) | cs.CL | This paper describes an experimental approach to Detection of Minimal
Semantic Units and their Meaning (DiMSUM), explored within the framework of
SemEval 2016 Task 10. The approach is primarily based on a combination of word
embeddings and parserbased features, and employs unidirectional incremental
computation of comp... | computer science |
14,990 | Speed-Constrained Tuning for Statistical Machine Translation Using
Bayesian Optimization | cs.CL | We address the problem of automatically finding the parameters of a
statistical machine translation system that maximize BLEU scores while ensuring
that decoding speed exceeds a minimum value. We propose the use of Bayesian
Optimization to efficiently tune the speed-related decoding parameters by
easily incorporating s... | computer science |
14,991 | Clustering Comparable Corpora of Russian and Ukrainian Academic Texts:
Word Embeddings and Semantic Fingerprints | cs.CL | We present our experience in applying distributional semantics (neural word
embeddings) to the problem of representing and clustering documents in a
bilingual comparable corpus. Our data is a collection of Russian and Ukrainian
academic texts, for which topics are their academic fields. In order to build
language-indep... | computer science |
14,992 | Exploring Segment Representations for Neural Segmentation Models | cs.CL | Many natural language processing (NLP) tasks can be generalized into
segmentation problem. In this paper, we combine semi-CRF with neural network to
solve NLP segmentation tasks. Our model represents a segment both by composing
the input units and embedding the entire segment. We thoroughly study different
composition ... | computer science |
14,993 | M$^2$S-Net: Multi-Modal Similarity Metric Learning based Deep
Convolutional Network for Answer Selection | cs.CL | Recent works using artificial neural networks based on distributed word
representation greatly boost performance on various natural language processing
tasks, especially the answer selection problem. Nevertheless, most of the
previous works used deep learning methods (like LSTM-RNN, CNN, etc.) only to
capture semantic ... | computer science |
14,994 | An Attentive Neural Architecture for Fine-grained Entity Type
Classification | cs.CL | In this work we propose a novel attention-based neural network model for the
task of fine-grained entity type classification that unlike previously proposed
models recursively composes representations of entity mention contexts. Our
model achieves state-of-the-art performance with 74.94% loose micro F1-score on
the wel... | computer science |
14,995 | Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term
Memory Models and Auxiliary Loss | cs.CL | Bidirectional long short-term memory (bi-LSTM) networks have recently proven
successful for various NLP sequence modeling tasks, but little is known about
their reliance to input representations, target languages, data set size, and
label noise. We address these issues and evaluate bi-LSTMs with word,
character, and un... | computer science |
14,996 | Efficient Calculation of Bigram Frequencies in a Corpus of Short Texts | cs.CL | We show that an efficient and popular method for calculating bigram
frequencies is unsuitable for bodies of short texts and offer a simple
alternative. Our method has the same computational complexity as the old method
and offers an exact count instead of an approximation. | computer science |
14,997 | Syntactic and semantic classification of verb arguments using
dependency-based and rich semantic features | cs.CL | Corpus Pattern Analysis (CPA) has been the topic of Semeval 2015 Task 15,
aimed at producing a system that can aid lexicographers in their efforts to
build a dictionary of meanings for English verbs using the CPA annotation
process. CPA parsing is one of the subtasks which this annotation process is
made of and it is t... | computer science |
14,998 | A Deep Neural Network for Chinese Zero Pronoun Resolution | cs.CL | Existing approaches for Chinese zero pronoun resolution overlook semantic
information. This is because zero pronouns have no descriptive information,
which results in difficulty in explicitly capturing their semantic similarities
with antecedents. Moreover, when dealing with candidate antecedents,
traditional systems s... | computer science |
14,999 | Dialog-based Language Learning | cs.CL | A long-term goal of machine learning research is to build an intelligent
dialog agent. Most research in natural language understanding has focused on
learning from fixed training sets of labeled data, with supervision either at
the word level (tagging, parsing tasks) or sentence level (question answering,
machine trans... | computer science |
15,000 | Speaker Cluster-Based Speaker Adaptive Training for Deep Neural Network
Acoustic Modeling | cs.CL | A speaker cluster-based speaker adaptive training (SAT) method under deep
neural network-hidden Markov model (DNN-HMM) framework is presented in this
paper. During training, speakers that are acoustically adjacent to each other
are hierarchically clustered using an i-vector based distance metric. DNNs with
speaker depe... | computer science |
15,001 | Chinese Song Iambics Generation with Neural Attention-based Model | cs.CL | Learning and generating Chinese poems is a charming yet challenging task.
Traditional approaches involve various language modeling and machine
translation techniques, however, they perform not as well when generating poems
with complex pattern constraints, for example Song iambics, a famous type of
poems that involve v... | computer science |
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