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<s>and key phrases depending on semantic and syntactic relationship among them [11].Moreover, the complexity of Bengali grammar and ambiguities in sentence structures raise thechallenges for working in Bengali. However, recent interest of the researchers in the field ofBengali opens a wide variety of scopes to work.Dom... |
<s>are listed as followings:1. To generate a rule based parse tree generator for the Bengali language to break the text intoclauses and deconstruct the clauses into key phrases that will be used as input to conceptextractor.2. To develop a method to extract the concept from the parse tree that is likely to expresssenti... |
<s>traversal in the reverse order is executed starting from theconcepts to the root of the parse tree of the sentence. Here, the rules are highly sensitiveto the dependencies that were detected in the earlier stage. The modifiers are very crucialto handle as these can alter the polarity of the sentence at any stage of ... |
<s>word co-occurrence counts butrely on the emotion categorization to detect polarity.The contributions can be more visualized over the possible outcomes of the thesis. A set of toolsand models with their specific capabilities are developed based on this work. The outcome ofthis thesis are listed as follows:1. A semant... |
<s>Works on sentiment analysis in Bengaliwill be discussed in Section 2.3 and scope of the works found through related works will behighlighted in Section 2.4. Finally, an endeavor will be made to formulate the research questionsin Section 2.5 to be address in this work.2.1 Sentiment AnalysisExisting works in sentiment... |
<s>polarity in different domains or contexts. For instance, an observation waspresented in [26] that “unpredictable” is a positive description for a movie plot, but a negativedescription for a car’s steering abilities. Without prior knowledge of context, there is probablyno way to determine the semantic orientation of ... |
<s>it fails to handle the influence of modifiers which can change the valence of the featureswithin the domain.Existing works using CRF, demonstrate that it performs well for aspect based sentiment analysis.For example, with CRF, sentiment classification has been performed in sentence and documentlevel in [31]; the wor... |
<s>resource named WordNet-Affect [7] has been presentedfor the lexical representation of affective knowledge from WordNet.Efficiency of concept-level sentiment analysis depends on anticipating the affective valenceof unknown multi-word expressions. In the significant work [3], a new data-set is built upby applying blen... |
<s>method using hourglass emotions. On the contrary, affective space provide auniform association among the concepts within the space. Therefore, determining the conceptvalence from affective information rather than emotion categorization will provide a simplerand efficient polarity detection model. Moreover, an attemp... |
<s>Bengali NLP taskover the years. Most of the works focus on generation of NLP tools like Bengali POS tagger,NER, sentence parser and to some extent of text categorization. A few number of NLP resourcesare also available, for example: Bengali SentiWordNet, WordNetaffect, stop word list, etc.A computational technique f... |
<s>Firstly, the poor recognitionof opinion words when modifiers are involved in influencing the sentiment valence of thesentence. A modifier can turn the polarity of an opinion word or phrase from neutral tonegative or positive. Secondly, reliance on surface features ignoring the affective associationamong the words wi... |
<s>within the language.[RQ2] What genetic factors should be considered in determining the constituents of the languagefor sentiment analysis and, how can those be adopted to extract from text?Researchers have introduced different levels of text constituents like lexicons, keywords,concepts, key phrases, even clauses an... |
<s>language. Lexicon resources are illustrated in a machine readable format that can beinterpreted by the computational application, such as,WordNet. Instead of a definition,WordNetuses the synonymy to represent the relationships among the words or lexicons, as between shutand close or car and automobile. Synonyms are ... |
<s>BrownCorpus annotated with POS tag is highlighted below:Daniel/np personally/rb led/vbd the/at fight/nn for/in the/at measure/nn,/, which/wdt he/pps had/hvd watered/vbn down/rp considerably/rb since/inits/pp$ rejection/nn by/in two/cd previous/jj Legislatures/nns-tl ,/,in/in a/at public/jj hearing/nn before/in the/a... |
<s>entity itself as a whole, we use the special aspect GENERAL to denote it[Stated at[8]].In NLP, an opinion generally consists of five components mentioned in Definition 5. However,it can vary depending on the application. For example, sometimes, it is not necessary to knowthe opinion holder if the task is to summariz... |
<s>punctuation marks, articles, and prepositions, such as3.2. NLP TECHNIQUES 25‘the’, ‘a’, ‘and’ etc. These tokens are sometimes, called stop words and removed from thecorpus, as they do not generally contribute greatly to the semantic evaluation of the content.As a fundamental technique, many tokenization tools are av... |
<s>In the context of sentiment analysis, theparser plays a very influential role to form the concepts from the corpus, hence, extract thedependencies among them as discussed in Section 3.1.4. One of the enhanced version of it issemantic dependency parser. To be mentioned, the Stanford dependency parser is an examplefor... |
<s>the affective information inside the synsets was performed. The resultshave shown that the synsets are a good model for the representation of affective concepts.3.3.3 AffectiveSpaceThe latest form of the knowledge base in the field of emotion reasoning is the AffectiveSpace.In [3], a blending technique was applied o... |
<s>the vectors in U and V that are more significant components of the initial Amatrix. A tranculated SVD can be created with a reduced number of singular value p followingEquation (3.3):aij ≈k=1uikskvjk (3.3)where p < n is the number of singular values that will remain.Equation (3.3) can be used for data compression by... |
<s>correlated and uncorrelated Gaussian distribution.To accommodate multiple predictors, the discriminant equation remains the same but it isexpressed using vector notation as Equation (3.9):δk(x) = xT−1∑µk −−1∑µk + log(Πk) (3.9)3.4. MATHEMATICAL MODELS 32Figure 3.5: Boundary line to separate 2 classes using LDA.Figure... |
<s>positive, negative and neutral. This step is termed as functiongenerator for concept level polarity detection which generates the polarity detection functionusing the classification function coefficient values produced by LDA for each class. Finally,concepts extracted from the corpus are mapped to affective space to... |
<s>other hand, the word tag‘নয় /VM’ ([nOi], not) is wrongly tagged as ‘VM’ which should be a negation(NEG) annotation.Thereby, we get a more comprehensive annotation of the aforementioned sentence as under:[ ইভ/JJ িটিজং/NN বা/CC উ তার/NN িশকার/VM হেল/VAUX কারও/PRP সংেকাচ/VMকরা/VAUX উিচত/RB নয়/NEG ]To limit the scope of... |
<s>(MOD/NEG)/CC add to subject and repeat theprocess, else Parse as subject.(c) Parse the rest of the sentence except subject as object.[RULE- 3] Parse the Subject into tokens:(a) If the subject is a single word parse into a single token.(b) If any MOD/NEG is present parse associated token with MOD/NEG, else parse into... |
<s>of the modifiers or negationas it will reverse the polarity of the sentiment of the associated concept. On the other hand, ifthe negation is associated with the verb clause then, it will negate the overall sentiment of thesentence. Otherwise, if it is associated with an adjective or any other opinion word, it will o... |
<s>neither enhance the original meaning nor indicate any otherknowledge, therefore, it will not be considered as a concept. However, some of the tokens withPOS like a noun, adjective, and VM remaining stand lone can also be considered as a concept.4.4. CONCEPT EXTRACTION AND DEPENDENCY DETECTION 40The rules based on th... |
<s>“িশকার _হওয়া ” [Sikar hOa] and “সংেকাচ _করা ” [SNkotSkora] have been formed following the rule “MAIN VERB + AUXILIARY VERB”. Both theconcept represent some action like “to be victim of” and “to be ashamed of” respectively andcarry negative sentiment, whereas, ‘িশকার ’ ([Sikar], hunt) and ‘সংেকাচ ’ ([SNkotS], shame)s... |
<s>properties of truncated SVD to build theaffective space, the ‘eigenmood’ values of the concept nearer to each other within the space tendto be similar. To categorize the sentiment, our aim is to discriminate among the positive, negativeand neutral concepts based on their eigenvalues. In this context, LDA is an appro... |
<s>the concepts with their polarity determined by the concept level polaritydetector. Then, we traverse the tree from the concept node to the root following the rulesdescribed below.1. If any node contains one concept the node will be labeled the polarity of the concept.2. If any node contains two concepts then the pol... |
<s>5.4, we will evaluate theperformance of the model and represent some statistical data on experimental analysis. Finally,Section 5.5 will recapitulate the experimental analysis through an inquisitive discussion onperformance evaluation of the model.5.1 Experimental SetupIn this work, we implement our experiment using... |
<s>one from a Bengali news portalon law “LawyersClub Bangladesh.com”. The statistics of the corpus is highlighted in Table 5.2.As the method finally finds the polarity at sentence level using the polarity of the conceptsdetermined through the concept level polarity detection model, therefore, variation in theparagraph ... |
<s>score, takes both precisionand recall into account, and represents the balance between recall and precision. F1 Score is alsoviewed as the weighted average of precision and recall which is measured by the Equation (5.5).When one of the precision and recall is given emphasize over the other, the F1 score decreases.On... |
<s>term in asentence. Table 5.4 represents the performance of the concept extractor.Proposed method failed to extract very few concepts of which most of them are adverb notpositioned adjacent to the verb. Some of the auxiliary verbs sometime express the sentiment,hence, expected to be extracted as a concept. However, t... |
<s>efficiency of binary classification, the exclusionof neutral class may affect the efficiency in determining the sentence valence as many neutralconcepts will be considered as either positive or negative. Sometimes, it is cumbersome to dealwith the concepts which are neither positive nor negative.However, the binary ... |
<s>5.8. A system with high recall but low precision returns a high number of instancesfor desired class but many of the predictions are incorrect compared to their actual class. Asystem with high precision but low recall is just the opposite, returning very few results for thedesired class, but most of which are predic... |
<s>level both for simple sentences and the complex or compoundsentences.We observe that the accuracy for polarity detection of the simple sentences is higher than theaccuracy of complex or compound sentence. This is due to the complexity raised in the instanceswhere different parts of the complex or compound sentence c... |
<s>the latter part of this thesis, a concept level polarity detection model is introduced using alearning method which uses the AffectiveSpace as a knowledge base. The motivation behindusing the AffectiveSpace is to infer the semantic and affective information associated withnatural language opinions. Moreover, concept... |
<s>the sentence based on stem categories need to address to increase the6.3. SCOPE OF FUTURE WORK 60efficiency of the parser. Integration of morphological knowledge can have a great impacton the performance of the dependency parser.2. The concept extractor presented in this thesis extracts the concepts containing only ... |
<s>89, pp. 14–46, 2015.[9] S. Baccianella, A. Esuli, and F. Sebastiani, “Sentiwordnet 3.0: an enhanced lexicalresource for sentiment analysis and opinion mining,” in Lrec, pp. 2200–2204, 2010.[10] G. F. Simons and C. D. Fennig, “Ethnologue: Language of the World.” https://www.ethnologue.com/ethnoblog/gary-simons/welcom... |
<s>inProceedings of the 2008 international conference on web search and data mining, pp. 231–240, ACM, 2008.[28] B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up?: sentiment classificationusing machine learning techniques,” in Proceedings of the ACL-02 conference onEmpirical methods in natural language processing-Volu... |
<s>1, pp. 108–154, 2008.[48] A. Polguère et al., Dependency in linguistic description, vol. 111. John BenjaminsPublishing, 2009.[49] Robin, “Article on Natural Language Processing.” http://language.worldofcomputing.net/category/tokenization, Nov. 2009. (last accessed<Jan 19, 2019>).[50] A. Ekbal, R. Haque, and S. Bandy... |
<s>Semantic Textual Similarity in Bengali TextSee discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/329394770Semantic Textual Similarity in Bengali TextConference Paper · September 2018DOI: 10.1109/ICBSLP.2018.8554940CITATIONSREADS3082 authors:Some of the authors ... |
<s>terms existin these two sentences but there is an obvious semanticsimilarity. The table I depicts the scenario. However, thesetwo examples conclude that the lexical measures are notenough to capture the similarity.TABLE I: The weekness of lexical matching in capturingsemantic similaritySentence 1 Sentence 2 Similari... |
<s>p(wt|wt−k, ..., wt+k)A multiclass classifier is used for the prediction task,such as softmax [7].p(wt|wt−k, ..., wt+k) =eywt∑i ewhere each of yi is un-normalized log-probability for eachoutput i, computed asy = b+ Uh(wt−k, ..., wt+k;W )where U , b are the softmax parameters. h is constructedby a concatenation or ave... |
<s>Similarity MeasuringAlgorithm for Bengali TextsThis section presents our introduced algorithm formeasuring the semantic similarity between two sentencesS1 and S2. The Algorithm 1 presents the pseudo-code.The table II summarizes the basic notation used in ourproposed algorithm.TABLE II: Basic notation used in Algorit... |
<s>by human assessors’ judgments. We employedtheir provided gold-standard judgment as a ground truthin this research. Their human assessors have given thesimilarity score using the following similarity label rangesfrom [0, 5].• Label 0: On different topics• Label 1: Not similar but share few common details• Label 2: No... |
<s>has given 80% similarityfor first sentence-pair (“িতিন েতামােদর বাংলা িশক্ষক” and “িতিনেতামােদর বাংলা িশক্ষকেক িপিটেয়েছন”) but, the performance ofour method concludes that they are 33% similar. Based onthe semantic meaning of these two sentences, they are notsimilar but share few common information. Our proposedalgo... |
<s>andComputational Semantics-Volume 1: Proceedings of the mainconference and the shared task, and Volume 2: Proceedingsof the Sixth International Workshop on Semantic Evaluation.Association for Computational Linguistics, 2012, pp. 441–448.[12] D. Bär, C. Biemann, I. Gurevych, and T. Zesch, “Ukp: Comput-ing semantic te... |
<s>untitledSee discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/269297101New approach of solving semantic ambiguity problem of Bangla Root wordsusing universal networking language (UNL)Conference Paper · May 2014DOI: 10.1109/ICIEV.2014.6850778CITATIONSREADS8803 a... |
<s>4, we present our main works that include all the above three components. II. PROBLEM DEFINITION A. Structural Ambiguity A word, phrase, sentence or other communication is called ambiguous if it can be interpreted in more than one way. If the ambiguity is because of a multiple meanings of a word, it is called lexica... |
<s>eর পােয় পড়ল। Student teacher's legs were mistakes. rests Agt,man মা ঘিুমেয় পেড়েছ। Mother has fallen asleep. broken Obj,met ঘিড়িট পেড় েভে েগেছ। The clock has broken by falling down teach agt িশkক পড়ােcন। The teacher is teaching. Table 2: Bangla Ambiguous Sentence of Root Word “ধর ” Root word Meaning when used in sent... |
<s>immediate previous word [বািড়]. bZzb ােট K‡e hv‡eb? Here, root word [hv] and the immediate previous word [K‡e]. It needs to know semantically the use of root word in each sentence same root carry different meaning. For this it needs to analyze the words in the sentences before and after the main root/verb. The parse... |
<s>che(েছ) respectively. (c) If the suffixes (িবভিk) for 1st person is lam(লাম) or chilam (িছলাম) then the corresponding suffix (িবভিk) for 2nd person and 3rd person is l(ল) or chil(িছল) and le(েল) or chile(িছেল) respectively. (d) If the suffixes (িবভিk) for 1st person is bo(ব) then the corresponding suffix (িবভিk) for... |
<s>obj(fly(icl>occur,equ>pass,obj>thing).@entry.@present,time(icl>abstract_thing,equ>occasion)) man(fly(icl>occur,equ>pass,obj>thing).@entry.@present,like(icl>how,obj>thing)) obj(like(icl>how,obj>thing),arrow(icl>mark>thing).@indef) {/unl} [/S] 3. In put Bangla sentence: েস বiিট েটিবেলর uপের রাখল” [S:00] {org:en} He ke... |
<s>9, September-2012 ISSN 2229-5518. [13] Muhammad Firoz Mridha, Md. Zakir Hossain, Shahid Al Noor, “Development of Morphological Rules for Bangla Words for Universal Networking Language” IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.10, October 2010. [14] Muhammad Firoz Mridha, Kamru... |
<s>/CenturySchL-Roma /CenturySchoolbook /CenturySchoolbook-Bold /CenturySchoolbook-BoldItalic /CenturySchoolbook-Italic /CGTimes-Bold /CGTimes-BoldItalic /CGTimes-Italic /CGTimes-Regular /CharterBT-Bold /CharterBT-BoldItalic /CharterBT-Italic /CharterBT-Roman /CheltenhamITCbyBT-Bold /CheltenhamITCbyBT-BoldItalic /Chelt... |
<s>/Latha /LatinWide /LetterGothic /LetterGothic-Bold /LetterGothic-BoldOblique /LetterGothic-BoldSlanted /LetterGothicMT /LetterGothicMT-Bold /LetterGothicMT-BoldOblique /LetterGothicMT-Oblique /LetterGothic-Slanted /LetterGothicStd /LetterGothicStd-Bold /LetterGothicStd-BoldSlanted /LetterGothicStd-Slanted /LevenimMT... |
<s>/ColorImageDict << /QFactor 1.30 /HSamples [2 1 1 2] /VSamples [2 1 1 2] /JPEG2000ColorACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 10 /JPEG2000ColorImageDict << /TileWidth 256 /TileHeight 256 /Quality 10 /AntiAliasGrayImages false /CropGrayImages true /GrayImageMinResolution 200 /GrayImageMinResolutionPo... |
<s>See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/328333982A Deep Recurrent Neural Network with BiLSTM model for SentimentClassificationPreprint · September 2018CITATIONSREADS2,1291 author:Some of the authors of this publication are also working on these re... |
<s>social medias.Different organizations around the world are using the abilityto extract hidden data now-a-days. The change in sentimentscan be connected to the change in stock market. The Obamaadministration used opinion mining in the 2012 presidentialelection to detect the public opinion before the announcementof po... |
<s>keep on learning over several time steps.LSTMs consist of information outside the basic flow of thernn in a valved block [16].Fig. 2. LSTM UnitNeural network’s notes get triggered by the notes they get.Likewise, LSTM’s gates pass on or block the data based onits weight. After that, these signals are grated with thei... |
<s>considera-tion that, some one word comments have been dropped whichdo not express a specific sentiment. Some other informationscan be found in table I. If we have a look at the number ofunique words and the number of most occurrences, we cananticipate the distribution of words against their occurrences.On average ev... |
<s>their efforts in Bengali sentiment analysis. Also, we aregrateful to the researchers who have progressed the field ofNLP and Neural Networks. We acknowledge M. Al-Amin etal. for providing us with their dataset without which our workwould not be complete.REFERENCES[1] A. V. Yeole, P. Chavan, and M. Nikose, “Opinion m... |
<s>Signal Processing, vol. 45, no. 11, pp.2673–2681, 1997.View publication statsView publication statshttps://www.researchgate.net/publication/328333982</s> |
<s>Bengali VADER: A Sentiment Analysis Approach Using Modified VADER2019 International Conference on Electrical, Computer andCommunication Engineering (ECCE), 7-9 February, 2019Bengali VADER: A Sentiment Analysis ApproachUsing Modified VADERAl Amin, Imran Hossain, Aysha Akther* and Kazi Masudul AlamDGTED Lab, Computer ... |
<s>on the mostimportant languages for the future. They considered severaldifferent factors, one of them is languages spoken in thefastest-growing emerging economies by 2050. Out of theseemerging economies, Bengali is expected to be the third mostcommonly spoken language, lower than Chinese and Hindi[8].As a result, res... |
<s>usedthe architecture shown in Figure 1 to evaluate the sentimentof texts. The architecture mainly follows the steps describedbelow to calculate the polarity of the sentences:1http://sentiwordnet.isti.cnr.it/2http://hiztegiak.elhuyar.eus3VADER Sentiment, https://github.com/cjhutto/vaderSentimentEnglish TextPreprocess... |
<s>present in the text, then the polarity of thetext is reversed to either positive or to negative. Some examplewords are:(1) `না', `িন', `নয়', `নাই', `েনই'2) Booster Dictionary: Booster dictionary contains Bengaliwords that are used to boost valence of any text. If any oneof them are present in the text then polarity ... |
<s>to boost a word valence. Example of trigram:(14) `খুব েবিশ ভয়', `েবিশ ভয় পায়', `ভয় পায় িন'For any word, if the boosting word is found in the booster dic-tionary, then for bigram the valence of the token is multipliedby 0.9, and for trigram, it is multiplied by 0.75 [9].3) Negation: Usually, overall sentiment of a se... |
<s>of itstranslators though in Bengali it is a negative sentence. Whereasour proposed Bengali VADER gives the correct polarity ofthe sentence and determines it as a negative sentence. For theBengali sentence `িবেদিশ সাহােয র গিত বা েল আর রাজ আদােয়রবৃি বা েল ঋেণর পিরমাণ কেম আসেব ।' VADER detects thesentence as negative ... |
<s>et al., “Recognizing bangla grammarusing predictive parser,” arXiv preprint arXiv:1201.2010, 2012.[6] M. A. Islam, K. A. Hasan, and M. M. Rahman, “Basic hpsg structurefor bangla grammar,” in Computer and Information Technology (ICCIT),2012 15th International Conference on. IEEE, 2012, pp. 185–189.[7] K. A. Hasan, A.... |
<s>banglatext using contextual valency analysis,” in Computer and InformationTechnology (ICCIT), 2014 17th International Conference on. IEEE,2014, pp. 292–295.[26] S. Chowdhury and W. Chowdhury, “Performing sentiment analysis inbangla microblog posts,” in Informatics, Electronics & Vision (ICIEV),2014 International Con... |
<s>Sentiment Analysis on Movie Review Data Using Machine Learning ApproachInternational Conference on Bangla Speech and Language Processing (ICBSLP), 27-28 September, 2019 978-1-7281-5242-4/19 ©2019 IEEE Sentiment Analysis on Movie Review Data Using Machine Learning Approach Atiqur Rahman, Md. Sharif Hossen Dept. of In... |
<s>is following: The related investigation has been discussed in section II. Section III includes the analysis procedure of SA. Section IV discusses about various types of machine learning algorithm. Section V describes the experimental results. Section VI includes the summary and future endeavor. II. RELATED WORK This... |
<s>based lexicon, like as SenticNet [23] can acquire more appropriate sentiment outcome as it is context oriented instead of accord of words oriented. Semantic oriented concept was applied based on a concept net lexicon. In [24] the authors show a statistical approach to find the sentiments. Authors of [25] show the 2 ... |
<s>most recognizable used classifier. It considers that every feature is distinct from one another. NB classifiers are a collection of classifications algorithm which is not a standalone algorithm but a family of algorithm. The mathematical expression is as follows: ( | ) = ( | ) ( )( ) Where ( | ) = ( | ) ( | ) … ( | ... |
<s>where 1000 is negative and remaining is positive. We use the terms, namely, true positive (U), false positive (V), true negative (X), false negative (Y) for analysis. Here, first and second terms indicate that the review is really positive and negative respectively but both are featured as positive term. Third and f... |
<s>the movie review site. Next, we perform pre-processing on data by using NLP tool. Then, after creating features vector the data set is trained using ML classifiers, namely, Multinomial NB, Bernoulli NB, SVM, Maximum Entropy and Decision Tree classifiers which are tested using test dataset. Finally, we show our exper... |
<s>you? sentiment analysis on medical forums,” In Proc. of ICNLP, Asian Federation of Natural Language Processing, Nagoya, Japan, pp. 667–673, 2013. [19] S. A. Mahtab, N. Islam, M. Rahman, “Sentiment analysis on bangladesh cricket with support vector machine,” In Proc. of ICBSLP, 2018. [20] T. P. Sahu, Sanjeev Ahuja, “... |
<s>/BookshelfSymbolTwo-Regular /Botanical /Boton-Italic /Boton-Medium /Boton-MediumItalic /Boton-Regular /Boulevard /BradleyHandITC /Braggadocio /BritannicBold /Broadway /BrowalliaNew /BrowalliaNew-Bold /BrowalliaNew-BoldItalic /BrowalliaNew-Italic /BrowalliaUPC /BrowalliaUPC-Bold /BrowalliaUPC-BoldItalic /BrowalliaUPC... |
<s>/Helvetica-Condensed-Black /Helvetica-Condensed-BlackObl /Helvetica-Condensed-Bold /Helvetica-Condensed-BoldObl /Helvetica-Condensed-Light /Helvetica-Condensed-LightObl /Helvetica-Condensed-Oblique /Helvetica-Fraction /Helvetica-Narrow /Helvetica-Narrow-Bold /Helvetica-Narrow-BoldOblique /Helvetica-Narrow-Oblique /H... |
<s>/WP-BoxDrawing /WP-CyrillicA /WP-CyrillicB /WP-GreekCentury /WP-GreekCourier /WP-GreekHelve /WP-HebrewDavid /WP-IconicSymbolsA /WP-IconicSymbolsB /WP-Japanese /WP-MathA /WP-MathB /WP-MathExtendedA /WP-MathExtendedB /WP-MultinationalAHelve /WP-MultinationalARoman /WP-MultinationalBCourier /WP-MultinationalBHelve /WP-... |
<s>Sentiment Extraction From Text Using Emotion Tagged CorpusSentiment Extraction From Text Using EmotionTagged CorpusThasina TabashumComputer Science and EngineeringAmerican International University Bangladeshthasinatabashumabonti@gmail.comAbdul Mutalab ShaykatComputer Science and EngineeringAmerican International Uni... |
<s>product recommendation system [5],determining the subjective adjectives [6], topic detection andidentifying the pilot of the study [7] are focused on text pro-cessing. As the importance of opinion mining is increasing dayby day in many sectors of modern life, new methods are beingintroduced and researchers are impro... |
<s>satisfaction JYFurious AG rejoicing JYDistasteful DG regard JYDisgustful DG amaze SPUnassertiveness FR astonish SPIV. DATA ANALYSISIn this section, our objective is to label the unlabeledwords. To achieve this, the words were tagged on both anautomatic and manual level. Therefore this method of emotiontagging ultima... |
<s>with the maximum P.Evalue that was found for a single word. Taking maximum P.E"punishment" has been tagged as "DG". The total number ofwords tagged summed up to 247.TABLE IVNUMBER OF WORDS WITH EMOTION TAGEmotion Tag JY SP SD FR DG AGNumber of Words 16 33 77 12 64 43B. Non-Automatic Word TaggingThe same article is p... |
<s>0 2 1SD 0 0 23 0 1 0FR 0 0 1 15 2 0DG 0 0 0 0 23 0AG 1 0 0 0 2 18Therefore, when given an article with a positive toneafterward, it was unable to accurately determine the overallsentiment of the article. This proved that word level evaluationis not sufficient, and the analysis must be done on a contextuallevel as we... |
<s>’Neutral’ The proposedmethod would create a tree where only parts of speech tags-noun, adjective, verb, adverb shall be considered. If pos =Nounthat won’t create another child branch under it. Like in figure2 under "Unwrap", there are "shroud", "face", "baby". Sincethey are nouns, a child is not created until the wo... |
<s>reaching the startingnode "Authorities", it travels the existing data tree withoutvisiting same node again. Distance is measured with belowequation:dis =...(4), En = numberofedgetraveled.IEEE - 4567010th ICCCNT 2019 July 6-8, 2019, IIT - Kanpur Kanpur, IndiaFig. 5. Distance form a node to other nodes in contextual t... |
<s>with Applications, 72, 221âĂŞ230.https://doi.org/10.1016/j.eswa.2016.10.065[9] Hasan, K. M. A., Sabuj, M. S., and Afrin, Z. (2015). Opinion Min-ing using Naive Bayes. 2015 IEEE International WIE Conference onElectrical and Computer Engineering (WIECON-ECE), 511âĂŞ514.https://doi.org/10.1109/WIECON-ECE.2015.74439... |
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<s>Sentiment Analysis on Bengali Text using Lexicon Based Approach978-1-7281-5842-6/19/$31.00 ©2019 IEEE 2019 22nd International Conference on Computer and Information Technology (ICCIT), 18-20 December, 2019 Sentiment Analysis on Bengali Text using Lexicon Based Approach Abstract—In this modern era, we daily involve i... |
<s>influence for businesses as well as Government offices. To avoid unwanted circumstances, it is important for the Government to understand the public sentiments as well as be updated about political agendas. In this paper, we have developed a polarity detection system on Bengali textual opinions/reviews like as produ... |
<s>words was used to find the sentiment polarity of the sentence. 91% accurate results were achieved for the classification of news articles. In [14] authors proposed for the unigram presence method with negation handling and stemming. This proposed system obtained average accuracy but showed low performance. A polarit... |
<s>‘পােরন’ 3) Stop words Remove: Stop words are used to complete a sentence but it has no importance in sentiment analysis. Normally in sentiment analysis, stop words are removed [18]. Boost Word CheckNegation Check Total Sentiment Score of Text Calculation Bengali Text (Reviews/Opinions) Bengali Sentiment Words Dictio... |
<s>the next word ‘ভােলা’ and ‘ভােলা’ is a positive sentiment word. Then ‘aেনক’ increases the positivity of the text line. 3) Negation Check: Naturally, in Bengali text, negation words are placed at the end of the text line. We have developed a list of Bengali negation words such as ‘নয়’, ‘েনi’, ‘না’, ‘নাi’, ‘িন’. If an... |
<s>equal to -1 (-1 <= Normalize score < 0), then the text line is predicted as negative. Otherwise, the text is neutral. Some predicted reviews/opinions by our proposed system are shown in Table I. 1https://github.com/Fighter-1/Programming-/tree/master/Dictionary 2https://www.nltk.org/_modules/nltk/sentiment/vader.html... |
<s>Fig. 3. Visualization of accuracy comparison in bar diagram. TABLE III. PERFORMANCE COMPARISON OF OUR PROPOSED SYSTEM AND MACHINE LEARNING CLASSIFIERS. 3https://scikit-learn.org Method Accuracy (%) Proposed System 92% Decision Tree Classifier 87% Naive Bayes Classifier 86% Support Vector Machine Classifier 88% Metho... |
<s>Computer and Information Technology (ICCIT), 2014, pp. 292–295. [6] T. S. Utomo, R. Sarno and Suhariyanto, “Emotion Label from ANEW Dataset for Searching Best Definition from Wordnet,” IEEE International Seminar on Application for Technology of Information and Communication (ISEMANTIC), 2018, pp. 249-252. [7] A. Aga... |
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