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<s>tests such as fluency and adequacy tests. To ensure the quality ofoutput, the Bilingual Evaluation Understudy(BLEU) score has been calculated. Some Bangla phrasesgenerated with their respective UNL phrases by the proposed Bangla DeConverter are shown inTable 3. Our proposed system achieved a BLEU score of 0.76. Sinc... |
<s>No. Input UNL Expressions Bangla Sentences Produced by Bangla DeConverter{unl}agt(spend(icl>pass>do,com>time,).@entry.@past,i(icl>person))pos(holiday(icl>leisure>thing,equ>vacation),i(icl>person))obj(spend(icl>pass>do,com>time).@entry.@past,holiday(icl>leisure>thing,equ>vacation))plc(holiday(icl>leisure>thing,equ>va... |
<s>Bista, K. UNL Nepali DeConverter. In Proceedings of the 3rd International Conference onCALIBER, Cochin University of Science and Technology, Kochi, India, 2–4 February 2005; pp. 70–76.12. Singh, S.; Dalal, M.; Vachhani, V.; Bha acharyya, P.; Damani, O.P. Hindi generation from Interlingua (UNL).In Proceedings of the ... |
<s>Emotion Detection from Bangla Text Corpus Using Naïve Bayes Classifier4th International Conference on Electrical Information and Communication Technology (EICT), 20-22 December 2019, Khulna, Bangladesh 978-1-7281-6040-5/19/$31.00 ©2019 IEEE Emotion Detection from Bangla Text Corpus Using Naïve Bayes Classifie... |
<s>around 33,996,0002. Nowadays, a large number of people use Bangla to write on social media. For this rapid growth of Bangla users, it is quite important to focus on the study of emotion detection in Bangla Language. Most of the recent works in Bangla focuses on binary sentiment analysis. A lot of works has been done... |
<s>focuses on the identification of the emotional expressions at word, phrase, sentence, and document level along with the emotion holders and events. Emotions has been tracked on the basis of subject or event. They observed a micro F-score of 0.63 on 200 test sentences that are collected from Bangla news and blogs for... |
<s>1. Dataset Preparation 2. Pre-processing 3. Feature Selection and Extraction 4. Classification Fig 1: Architecture of the proposed method A. Dataset Preparation The dataset we used for this work contains a large number of user comments from different Facebook groups and some public posts of popular bloggers. The com... |
<s>step to detect emotion because it affects the overall result of the work. A good feature selection results in a good prediction. So, selecting features properly to enhance the classification is very important. After the completion of the pre-processing phase, we applied several features to evaluate our processed dat... |
<s>We have applied it in our work using scikit-learn [11]. It is a widely used library for text classification in python. In our implementation, we used the Multinomial version of the NB which is defined by the function in scikit-learn as MultinomialNB(). It uses the fit(trainDoc, trainClass) method to train the classi... |
<s>while for sad categories, our model performed poorly. This is due to the fact that our training dataset was imbalanced and the sad class had the lowest number of training examples. However, this, in essence, represents the real-world scenario making our model more generalized. TABLE IV. DETAILED EVALUATION USING BES... |
<s>fine grained tagging at sentence level,” in Proceedings of the Eighth Workshop on Asian Language Resouces, 2010, pp. 47–55. [7] D. Das, “Analysis and tracking of emotions in english and bengali texts: a computational approach,” in Proceedings of the 20th international conference companion on World wide web, 2011, pp... |
<s>/BiffoMT /BinnerD /BinnerGothic /BlackadderITC-Regular /Blackoak /blex /blsy /Bodoni /Bodoni-Bold /Bodoni-BoldItalic /Bodoni-Italic /BodoniMT /BodoniMTBlack /BodoniMTBlack-Italic /BodoniMT-Bold /BodoniMT-BoldItalic /BodoniMTCondensed /BodoniMTCondensed-Bold /BodoniMTCondensed-BoldItalic /BodoniMTCondensed-Italic /Bo... |
<s>/GillSans-BoldItalic /GillSans-Condensed /GillSans-CondensedBold /GillSans-Italic /GillSans-Light /GillSans-LightItalic /GillSansMT /GillSansMT-Bold /GillSansMT-BoldItalic /GillSansMT-Condensed /GillSansMT-ExtraCondensedBold /GillSansMT-Italic /GillSans-UltraBold /GillSans-UltraBoldCondensed /GloucesterMT-ExtraConde... |
<s>/URWGothicL-BookObli /URWGothicL-Demi /URWGothicL-DemiObli /URWPalladioL-Bold /URWPalladioL-BoldItal /URWPalladioL-Ital /URWPalladioL-Roma /USPSBarCode /VAGRounded-Black /VAGRounded-Bold /VAGRounded-Light /VAGRounded-Thin /Verdana /Verdana-Bold /Verdana-BoldItalic /Verdana-Italic /VerdanaRef /VinerHandITC /Viva-Bold... |
<s>Aspect Extraction from Bangla Reviews using Convolutional Neural Network2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision& Pattern Recognition (icIVPR)Aspect Extraction from Bangla Reviews usingConvolutional Neural NetworkMd.... |
<s>Based Sentiment Analysis (ABSA) identifies the aspects of a given document and the sentiment expressed towards each aspect. ABSA is the most detailed version of sentiment analysis that discovers desired information from a document.There are two major tasks to perform aspect based sentiment analysis. 1) extract the p... |
<s>‘food’ and ‘price’. They annotate the polarity on an overall review that is ‘positive’.SemEval 2014 evaluation campaign [4] extends their dataset adding more three fields with aspect category. Datasets of sev-eral languages are published in semeval 2016 workshop [16], these are English, French, Russian, Arabic, Turk... |
<s>to get the prior valence(i.e. polarity) of each Bangla word. A dataset of Bangla textis proposed in [28] for sentiment analysis task. Long ShortTerm Memory (LSTM) of deep recurrent model is applied ontheir dataset. Only 850 Bangla comments are collected in [29]and Convolutional Neural Network (CNN) is used to classi... |
<s>compared to theaverage pooling. The max pooling is used in our model whichreturn the maximum value of every feature map.D. Output layerThe eventual features, produced from the penultimate pool-ing layer, are passed to a fully connected layer that generateoutputs over each aspect. We determine a threshold f andchoose... |
<s>was annotated by each participant. We calculated the majority voting to choose the final aspect category and the polarity of a comment. A part of the cricket dataset is given in Figure 3. The summary of the Cricket dataset are mentioned in table I.TABLE ITHE SUMMARY OF CRICKET DATASETAspect Category Polarity TotalPo... |
<s>32% accuracy respectively. So, in terms of accuracy we can say that use of Convolutional Neural Network in aspect extraction is the best option for these two proposed Bangla datasets.We can see from the result that the performances of the models are lower in both datasets. Different people think differently as well ... |
<s>in Proceedings of the Tenth InternationalConference on Language Resources and Evaluation LREC 2016,Portorož, Slovenia, May 23-28, 2016., 2016. [Online]. Available:http://www.lrec-conf.org/proceedings/lrec2016/summaries/61.html[6] A. Tamchyna, O. Fiala, and K. Veselovská, “Czech aspect-basedsentiment analysis: A ne... |
<s>analysis,”in Neural Networks (IJCNN), 2016 International Joint Conference on.IEEE, 2016, pp. 4465–4473.[21] K. Schouten, O. van der Weijde, F. Frasincar, and R. Dekker, “Super-vised and unsupervised aspect category detection for sentiment analysiswith co-cccurrence data,” IEEE transactions on cybernetics, 2017.[22] ... |
<s>TitleSee discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/311693706An Investigative Design Based Statistical Approach for Determining BanglaSentence ValidityArticle · December 2016CITATIONSREADS1845 authors, including:Some of the authors of this publication ar... |
<s>target language that can estimate the distribution of the language as accurately as possible. A SLM is a probability distribution P(s) over strings S that attempts to reflect how frequently a string S occurs as a sentence. The target text is regarded as invalid if the SLM probability score for it is below some thres... |
<s>a moderate success rate for only detecting correct sentences on a very tiny test set of 378 sentences. In a recent work [12], another n-gram based statistical method was proposed. In this work, rather than using frequency of POS tags of words the authors used n-gram frequency based probability analysis of words to t... |
<s>November 2016 These probabilities are normalized to be within the range of 0 to 1. 3.3 Zero Frequency Problem & Discounting No matter how large a training corpus is, it cannot cover a natural language entirely. There will always be some perfectly acceptable word sequences that are missing from the corpus. This means... |
<s>VOL.16 No.11, November 2016 Backoff language model is discussed next. 3.5 Backoff N-gram Language Model Introduced by Katz in 1987, Backoff (BO) language model [14] for n-grams is a non-linear method that builds an n-gram language model based on an (n-1)-gram model. BO model works on the principle that if a higher o... |
<s>n-gram frequencies into the backup storage for n = 1 to 4. 3. Compute the probabilities and backoff weights (if any) for all n-grams calculated in step 2 using appropriate LM and store them in the storage in arpa format. In this work, WB, BO and WBB all three models were trained for evaluation purpose. 4.3 Testing t... |
<s>4. In order to avoid model over fitting the training corpus was divided into two sets namely training set comprised of 80% of the data and held-out set IJCSNS International Journal of Computer Science and Network Security, VOL.16 No.11, November 2016 with rest of the 20% data. The trained LMs are tested on the held-... |
<s>for All Methods Methods Precision (PRCavg) Recall (RECavg) gram gram gram gram gram gram (existing) 66% 74% 80% 54% 73% 79% BO 63% 74% 79% 54% 73% 79% WBB 68% 76% 82% 55% 75% 81% As can be noticed from the Table 1, the precision for the grammatical data are quite low compared to recall values for all models. Whereas... |
<s>for the purpose of grammar checking, which provided better clarity and generalization of performance measures. We expect that our attempt will encourage other researchers to work on Bangla grammar verification which needs further attention as development in this research area is not yet up to the mark. In future, we... |
<s>M.S. degree in Computer Science and Engineering (Major in Intelligent Systems Engineering) and B.Sc. degree in Computer Science from North South University in 2009 and BRAC University in 2006, respectively. Now he is an Assistant Professor at the Department of Computer Science and Engineering in Daffodil Internation... |
<s>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/337199069A Technique For Perceiving Abusive Bangla CommentsArticle · July 2019DOI: 10.5281/zenodo.3544583CITATIONSREADS2252 authors:Some of the authors of this publication are also working on these related p... |
<s>NLP is sentiment analysis. Datascientists can evaluate comments on social mediausing sentiment analysis to see how their business’sbrand is performing, for example, or review notesfrom customer service teams to identify areas wherepeople want the company to perform better. Googleand other search engines use NLP deep... |
<s>Speech, Derogatory and Profanity categorizes.They used Vowpal Wabbits regression model tomeasure different aspects of the user comment andused N-grams, Linguistic, Syntactic features. Usingmulti-class classifier, [7] categorized tweets into hatespeech, offensive and neither of these two and differhate speech from of... |
<s>or objective and then further classifythe subjective tweets as positive, negative or neutral.They use a corpus of political tweets collected overthe UK pre-election period in 2010. For the taskof correctly identifying that a document contains apolitical sentiment and then correctly identifying itspolarity, they get ... |
<s>Bin Mortaza [23], Shakib Al Hasan [24],SalmoN TheBrownFish [25], Naila Nayem [26] andProthom Alo News Portal [27]. Only public commentsare collected without the commenters informationdue to protect privacy. In total, we collected 300comments as we will do the whole experiment man-ually. We have done the experiment i... |
<s>comparing the query terms with theindex terms (important words or phrases) that appearin the document itself. The decision may be binary(reclaim / reject) or may involve an assessment of thedegree of relevance that the document needs to query.Unfortunately, the words in documents and queriesoften have many structura... |
<s>of the data-set steps3 and 4 is taken3 Step 3:4 for Each words in the comment do5 if Word is not in the Term-Weight List then6 TotalWeightAbusive =TotalWeightAbusive + 07 TotalWeightNotAbusive =TotalWeightNotAbusive + 08 else9 TotalWeightAbusive =WeightAbusive + TotalWeightabusive10 TotalWeightNotAbusive =WeightNotA... |
<s>same way as in the generalclassification task.Fig. 8: Number of correct abusive, correct not abu-sive, wrong abusive and wrong not abusive class forthree sets of commentsIn a classification task, precision, recall, F-measureand accuracy are explained by four terms - true pos-itive, true negative, false positive and ... |
<s>V: Accuracy for the experiment resultSerialNumberof Com-mentsAccuracyAverageAccu-racy1 100 70%2 200 65% 68.93 300 71.7%From our experimental results in Table V, wecan say that using more comments is in fact veryeffective and offers promising performance for boththe proposed classifier algorithm.V. CONCLUSIONIn this ... |
<s>supervision,” CS224N Project Report,Stanford, vol. 1, no. 12, 2009.[12] A. Pak and P. Paroubek, “Twitter as a corpus for sentimentanalysis and opinion mining.” in LREc, vol. 10, no. 2010,2010, pp. 1320–1326.[13] D. Davidov, O. Tsur, and A. Rappoport, “Enhancedsentiment learning using twitter hashtags and smileys,”in... |
<s>research interests include Machine Learning,Artificial Intelligence, Software Engineering and Human ComputerInteraction . He is a Member of IEEE, Bangladesh ComputerSociety and Asian Business Consortium. He is also a member andteam leader of HCI research group of Computer science Departmentat Green University of Ban... |
<s>Implementation of Machine Learning to Detect Hate Speech in Bangla LanguageProceedings of the SMART–2019, IEEE Conference ID: 46866 8th International Conference on System Modeling & Advancement in Research Trends, 22nd–23rd November, 2019 College of Computing Sciences & Information Technology, Teerthanker Mahaveer U... |
<s>use Bangla language on Facebook. The Internet pack is getting cheaper day by day. The number of internet users is increasing. Now people of every part of Bangladesh are using Facebook. They are giving their analysis and views on different sectors. In this procedure there is a clash of thinking, liking, disliking. Wh... |
<s>the Twitter API to collect the data. For text analysis they have performed case folding, tokenizing, cleaning, stemming. They made a combination of LSTM with RNN. To find the result of the LSTM hidden layer they have used softmax regularization. They partitioned the data with different ratios at different times. At ... |
<s>Conference on System Modeling & Advancement in Research Trends, 22nd–23rd November, 2019 College of Computing Sciences & Information Technology, Teerthanker Mahaveer University, Moradabad, India319 Copyright © IEEE–2019 ISBN: 978-1-7281-3245-7 • Implementation of Machine Learning1). Pre-processingPre-processing mean... |
<s>the contrary, in neutral speech people were congratulation each other on different occasions. They were giving suggestion to each other on different topics. 3). Feature ExtractionWe have extracted the feature with count vectorizer and Term frequency-inverse document frequency vectorizer. The count vectorizer tokeniz... |
<s>0.73 0.70 0.71হ্যাঁ 0.68 0.70 0.69After applying Naïve Bayes, we got accuracy of 72% andTable 3: Test Results with Naïve BayesPrecision Recall F1-scoreনা 0.75 0.71 0.73হ্যাঁ 0.70 0.74 0.72V. ConclusionIn our work, we made a new dataset in the Bangla language. We divided the dataset into two groups and labeled them. ... |
<s>©Daffodil International University USING SOCIAL NETWORKS TO DETECT MALICIOUS BANGLA TEXT CONTENT NADIM AHMED ID: 152-15-5869 This Report Presented in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Computer Science and Engineering Supervised By Ms Subhenur Latif Assistant Professor D... |
<s>acknowledge with due respect the constant support and patients of my parents. ©Daffodil International University ABSTRACT Social spam has rapidly increased over recent years. Facebook and YouTube contain the most spam content compared with other social media networks. This kind of spam contents like text messaging o... |
<s>users social identity. The initial intent of SNs was to facilitate the connection and sharing. So, People are heavily dependent on online interactions for communications. The increases in content in social media are responsible for the increases of social spams. But unfortunately, this wealth of information, as well... |
<s>160 million native Bangla speakers and huge amounts of Bangla texts are generated online. Most researches on Bangla texts are performed using news corpus and blogs which are basically extracted by scraping the websites. Another source of data is social media where the opinionated texts are shorter in length but they... |
<s>be easier to check the polarity; how much positive or negative the sentence is. After analyzing the text pattern, the sentence could be categorized according to the polarity it belongs to. In my research, I have mainly researched on how I can detect whether the sentence is spam or ham from a given Bengali text which... |
<s>and linear computational complexity which is comparable to that of more algorithms in spam filtering[8]. In their papers, Sahami et Al.[9] used a Naïve Bayes classifier with a multi-variate Bernoulli model, a form of NB which relies on Boolean attributes. On the other hand, Pantel and Lin[10] adopted the Multinomial... |
<s>In this research, I will analyze Bengali text from Facebook status, YouTube comments etc. for finding associated spam of each sentence like positive or negative. After identifying the polarity of each sentence I will then try to find spam text content of each sentence. 2.5 Challenges Detecting spam or ham from Bangl... |
<s>িক� �বিরেয় এেলা অপু িব�ােসর �গাপন িভিডও কথা �লা �খত টাইেপর মজা পাইিছ �দৗলতিদয়ার কম�র �গাপন িভিডও ছাগেলর িতন ন�র বা�া ভালই �সিলে��ট হইেতেছন। �ােমর যুবতী �মেয়রা �দখুন িক কের । �গাপন িভিডও ফাস িশি�ত নয় সুিশি�ত হও �জার যার মু�ুক তার িশ�ক ও ছা�ীর �গাপন িভিডও �দখুন বাংলা আমার অহংকার Whenever a Bangla Sentence is used as i... |
<s>required tagged data. I formatted our dataset into two column. One is “Text” that contain actual text data and the other is “Status” that contain value 0 or 1. Spam text is labeled as 1, and non-spam as 0. It’s recommended to apply a classification algorithm on cleaned carpus instead of noisy carpus. The noisy corpu... |
<s>Bayes should applied, depends on data. Multinomial naive Bayes treats features as event probabilities. It has been shown experimentally in [11] that Multinomial Naïve Bayes performs generally better than the Multivariate Bernoulli NB in text classification. Multinomial NB surprisingly performs even better if term fr... |
<s>of our system, I noticed that the bigger the number of sentences, the higher are the recall and precision. Therefore, I believe that the enrichment of our database of Bangla sentences can significantly enhance the results. After experimenting, I have found that a sentence may have spam, or it may be ham. Featuring t... |
<s>up their public pages on social networks and enhance their direct interaction with their customers through content sharing, commenting, or through any other feedback system. Celebrities, online sellers or institutional organization also publish their content for direct interaction. It is unfortunate that some spamme... |
<s>Case Study Implementation on Spam Corpora. Cases on ICT Utilization, Practice and Solutions. doi:10.4018/9781609600150.ch012 ©Daffodil International University [15] Schneider, K. (2005). Techniques for Improving the Performance of Naive Bayes for Text Classification. Computational Linguistics and Intelligent Text Pr... |
<s>CATEGORIZATION AND TRANSLATION OPERATING SYSTEM’S ASSISTANCE IN EXPLICATION OF DIFFERENT BANGLADESHI ACCENTSSee discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/342705915CATEGORIZATION AND TRANSLATION OPERATING SYSTEM'S ASSISTANCEIN EXPLICATION OF DIFFERENT BA... |
<s>Formal language including in speeches, news, announcements is in Cholit Bhasha. During Bengali standardization in late 19th and early 20th century, cultural elite mostly belong to regions like Kolkata, Hooghly, Howrah and Nadia. In both Bangladesh and west Bengal the standard today is based on West Central Dialect w... |
<s>by building up an APSG for examination of part and determining naturally. Utilizing this strategy proficient interpretation framework was manufactured that is quick contrasted with others [5]. In another exploration the mix of regular language and discourse preparing in Phi DM-Dialog and its cost-based plan of equiv... |
<s>spelled letter groupings. Various techniques got proposed to limit spelled letter portions and rename them with a particular letter recognizer [16]. Improvement report was set up for interpreter programming which mostly counterbalances the nonattendance of instructive devices that conference weakened, requirement fo... |
<s>to mirror the principal of word in a docket or corpus and is called Short Term Frequency-Inverse Document Frequency (TF-IDF). This factor has weightage in retrieving information, text mining and user modeling through hunting of this data. Term Frequency (TF) Frequency of a word which pops up in a docket divided by t... |
<s>and Information Technology Vol.8, No.3, pp.31-45, June 2020 Published by ECRTD- UK Print ISSN: 2054-0957 (Print), Online ISSN: 2054-0965 (Online) Subspace Discriminant comes after Bagged Tree which has highest training time. SVM categorizers are much slow in this regard. Fig 5 Fascinating features depicted here is t... |
<s>As we consider whole algorithm, the precise results were given by Linear SVM and gives the expected outcomes. This categorizer assists in classifying languages like Bangla of Bangladesh and Bangla of Western Bengal. This categorizer would prove useful in classifying other accents too and the differentiation of langu... |
<s>Spoken Dialogue Recognition," in European Conference on Speech Communication and Technology, Germany Carnegie Mellon University, Pittsburgh, USA, 1995. [17] B. Sarkar, K. Datta, C. D. Datta, D. Sarkar, S. J. Dutta, I. D. Roy, A. Paul, J. U. Molla and A. Paul, "A Translator for Bangla Text to Sign Language," in 2009 ... |
<s>MergedFileThesis No: CSER-M-18-06 A STUDY ON KNOWLEDGE EXTRACTION FROM OFFICIAL BANGLA DOCUMENTS Monika Gope Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna 9203, Bangladesh December, 2018 A Study on Knowledge Extraction from Official Bangla Documents Monika Gope R... |
<s>and a very few information. It is difficult because wide computational resources for Bangla are very limited. It is literally infeasible to list and analyze the Bangla data manually. Several approaches for identifying and extracting tables, figures, emotion, reviews, and algorithms have been done in English. Further... |
<s>Features 44 4.7.4 Classify the Documents with Keywords 44 4.8 Conclusion 45 CHAPTER V Results and Discussions 47 5.1 Experimental Setup 47 5.2 Performance Analysis of the Structure 47 5.2.1 Extraction of Agenda And Decisions Text Analysis 47 5.2.2 Finding User Query from the Extracted Decision Pool Analysis 5.3 Disc... |
<s>unlock the information embedded within this data that surround us, introduces new challenges [1]. To solve this problems various data mining techniques are developed and also faces various challenges. Data mining is a procedure that takes data as input and outputs knowledge [1]. Data mining is the nontrivial process... |
<s>Sentence Extraction with specific Features Patterns and Features Mining Knowledge 1.3 Problem Statement Identifying and extracting informative entities such as mathematical expressions [5], [6], tables of contents [7], [8], figures [9], [10], from documents have been studied widely. Bhatia, et al., recommended a set... |
<s>information from the tabular data. All experiments in done on a windows machine and we used Java and Python as programing languages to implement our algorithm and Weka [17] as an implementation tool. We have used nltk and other python packages. Naïve-Bayes Classifier model and Gaussian is used to classify the result... |
<s>from scanned documents. That is, it primary evinces the PDF document into an image before finishing layout analysis, segmentation and character and mathematical expression recognition. Great recognition rates can be obtained with digital PDF documents as they are moderately free of noise, consequently less disposed ... |
<s>between the two adjacent edges of any adjacent pair is in threshold class 0. This yields single characters or collections of characters, which form words or numbers. To linearize the two dimensional layout of the characters into a 1-dimensional version using guidelines of mathematical expression arrangement. The rul... |
<s>numbers related with the name of sections, sub-sections or articles/author. The page number is considered as word as a whole as the rightmost word of a text line [7]. However for TOC-I the right aligned page numbers will have their echo in the vertical projection in the form of a secluded narrow hump at the rightmos... |
<s>on multiple regularities based on numbering and ordering. Furthermore, they also studied bibliography extraction and citation parsing for a large dataset of books. Lastly, they used the multiple fields accessible in books to rank books in answer to search queries. The system can successfully extract metadata and con... |
<s>extracted automatically from these 2-D plots, thus removing a time consuming physical procedure. Their information extraction algorithm recognizes the axes of the figures, extracts text blocks like axes-labels and legends and finds data points in the figure. It also extracts the units appearing in the axes labels an... |
<s>by an integer that characterizes the document-element number. The integer is followed by a DELIMITER that can again be either “:” or “.”. The last non-terminal TEXT gives a textual explanation of the element. Identifying a grammar enables to follow a cohesive method for dealing with dissimilar types of document-elem... |
<s>captions of PCs. b) Machine Learning Based Method: These features are classified into 4 groups: Font-style based (FS), Context based (CX), Content based (CN), and Structure based (ST). c) Combined Method: They proposed a combined method rule based method and the machine learning based method. 2. Extracting Algorithm... |
<s>(2) Opinionated articles that clearly present authors’ and readers’ views, evaluation or judgment about some specific events or persons. In order to identify features we started with Part Of Speech (POS) categories and continued the exploration with the other features like chunk, functional word, SentiWordNet in Ban... |
<s>have explored the impact of thematic term feature and position feature on Bangla text summarization. They have compared the proposed method to the LEAD baseline which was defined for single document text summarization task. LEAD baseline considers the first 𝑛 words of an input article as a summary, where 𝑛 is a pr... |
<s>will be used to score aspirant keywords. They assessed several metrics for calculating word scores, based on the degree and occurrence of word vertices in the graph: 1) Word frequency, 2) Word degree and 3) Ratio of degree to frequency They followed the approach described in [36] using the testing set for assessment... |
<s>In [9], they uses information cues existing in the caption. It is a score assigned to each sentence grounded on its likeness with the caption. After elimination of stopwords from the caption sentence and stemming using Porter’s Algorithm [41], the subsequent keywords form a “query” which offers cues about the inform... |
<s>let 𝑈𝑘 be the Utility measure of sentence 𝑆𝑘 that expresses whether it is beneficial to select the sentence or not. It is explained as: 𝑈𝑘 = 𝑔(𝑘) − 𝑓(𝑘) (3.4) Here, 𝑔(𝑘) is a function that favors the selection of 𝑆𝑘 and 𝑓(𝑘) is another function contrasting the selection of 𝑆𝑘. Sentences for which u... |
<s>explanation [49]. F1 is typically more beneficial than accuracy, particularly for rough class distribution. Accuracy works great if false positives and false negatives have analogous cost. If the cost of false positives and false negatives are very dissimilar, it is preferable to focus at both Precision and Recall. ... |
<s>languages. 3.8 Mixture Models and the EM Algorithm [50] The Mixture Model algorithm is exhibited as a linear combination of 𝐶 component densities 𝑃(𝑚|𝑥) in the form ∑ 𝜋𝑚 𝑃(𝑚|𝑥), where the 𝜋𝑚 are called mixing coefficients, and characterize the prior probability of data point 𝑥 having been produced from c... |
<s>Extraction with features ().Extraction algorithm extracts all decisions and stored in the decision pool. From the decision pool the user query is found out by calling Decision Extraction with features algorithm. To identify the desired lines, we processed the document to get the pure text and then with the correspon... |
<s>the documents and Fig.4.6. Shows the algorithm respectively. The system takes the documents 𝐷𝑒𝑖 , a set of Bangla decision and Query 𝑄 and returns 𝑑𝑒𝑖 , a set of Bangla detected texts. For each query, the system collects the required lines with some semantics features explained in the following sub sections. ... |
<s>words from the files. 2) The PDFBox prints the sequence of text in the order they appeared in the document [14], [9]. Thus all the line in the text is given a sequence number for measuring the location of the sentences. 3) All the sentences are then extracted using stopword in Bangla (|) and Removing different punct... |
<s>because a line may contain this phrase as reference but not as a decision. Nevertheless, there are many lines which contains “decision” of the “agenda” under the “decision” phrase and don’t contain the phrase. That’s why we need to search for content and context based features. And for the user query, the same above... |
<s>the “decision” line. So we used the phrase “োসত করা হণে”, “জমা সিণত হণে”, “প্রপ্ররণ করণত হণে” etc. instead of only “হণে”. Fig. 4.8: Decision Making Phrases 4.4.3 Context-Based Features 1. All of the above similarity and matching processes only consider the content, even the rule or phrase mapping method. However, s... |
<s>However, if the there is a duplicate sentence then it is removed from the list. Example 4.4 The decision with the quotation marks is shown in the Fig. 4.11 which we have excluded from the list of decision. Fig. 4.11: Example 4.4 4.5 Ordering the Documents Chronologically All the files have a date at the beginning of... |
<s>graph of the words and relationships between them from a document, then finds the most important points of the words based on importance scores calculated from the entire words graph. We have used this algorithm to rank the sentences here. 4. Then we have selected the most common 20 keywords from these techniques. T... |
<s>“প্রসশিা ” then it can find words with “Sessional” also. In the 20 keyword knowledge base we have listed “অসডিিযান্স”, “গ্রাজণুয়ি”, “প্রমকাসিকযা ” , “প্ররজজণেশি” , “কসমটি”, “সথওরী” etc words. 2. Then, there are some English to Bangla words which are used simultaneously. Such as “তত্ত্বীয়” with theory, “প্রকাস ি প্রত... |
<s>these connection sentences, then the previous sentence is extracted with the current sentence. These connection words are mostly the first word of the sentence. However, they can be anywhere in the sentence according to the context. So we have considered these words are location independent in the sentence. 4.7.4 Cl... |
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