nach oben

The Journal of Supercomputing

Erschienen in:

13.07.2016

AspectFrameNet: a frameNet extension for analysis of sentiments around product aspects

verfasst von: Sanjay Chatterji, Nitish Varshney, Ranjan Kumar Rahul

Erschienen in: The Journal of Supercomputing | Ausgabe 3/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

In the real-world scenarios, customer tries to evaluate a product based on sentiments conveyed by its users or reviewers. AspectFrameNet provides a framework that helps the semantic analysis of text inputs from social feeds and news (Voice of Customer) by disambiguating the contexts in which the lexical units are used. To this end, we have used this framework in analysing sentiments around different aspects of internet of things. We have tested this framework for 31 interrelated aspects in mobile domain and three possible sentiments (positive, negative and neutral).

Vorheriger Artikel Development of an ultra-HD HEVC encoder using SIMD implementation and fast encoding schemes for smart surveillance system

Nächster Artikel Internet of surveillance: a cloud supported large-scale wireless surveillance system

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

The Stanford tools and guidelines are downloadable from: http://nlp.stanford.edu/software/.

The ARK-Tweet-NLP tools of CMU are downloadable from: http://www.ark.cs.cmu.edu/TweetNLP/.

CRF++: Yet Another CRF toolkit Version 0.58 has been downloaded from: http://crfpp.googlecode.com/svn/trunk/doc/index.html?source=navbar#download.

LIBSVM Version 3.20 has been downloaded from: http://www.csie.ntu.edu.tw/~cjlin/libsvm/.

Baccianella S, Esuli A, Sebastiani F (2010) Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In: Chair NCC, Choukri K., Maegaard B, Mariani J, Odijk J, Piperidis S, Rosner M, Tapias D (eds) Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10). European Language Resources Association (ELRA), Valletta, Malta

Baker CF, Fillmore CJ, Cronin B (2003) The structure of the FrameNet database. Int J Lexicogr 16(3):281–296CrossRef

Breiman L (2001) Random forests. Mach Learn 45(1):5–32. doi:10.1023/A:1010933404324 CrossRefMATH

Brody S, Elhadad N (2010) An unsupervised aspect-sentiment model for online reviews. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, Los Angeles, California, pp 804–812

Brun C, Popa DN, Roux C (2014) Xrce: Hybrid classification for aspect-based sentiment analysis. In: Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). Association for Computational Linguistics and Dublin City University, Dublin, Ireland, pp 838–842

Chang C, Lin C (2011) LIBSVM: A library for support vector machines. ACM TIST 2(3):27

Chen Z, Mukherjee A, Liu B (2014) Aspect extraction with automated prior knowledge learning. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, vol 1. ACL, Baltimore, pp 347–358 (Long Papers)

Cruz IVAN, Gelbukh A, Sidorov G (2014) Implicit aspect indicator extraction for aspect based opinion mining. Int J Comput Linguist Appl 5(2):135–152

De Marneffe MC, MacCartney B, Manning CD et al (2006) Generating typed dependency parses from phrase structure parses. Proc LREC 6:449–454

10.

Dolbey AE (2009) Bioframenet: a framenet extension to the domain of molecular biology. Ph.D. thesis, University of California, Berkeley

11.

Eibe IW, Witten IH, Frank E, Trigg L, Hall M, Holmes G, Cunningham SJ (1999) Weka: Practical machine learning tools and techniques with java implementations. In: Proc ICONIP/ANZIIS/ANNES99 Future Directions for Intelligent Systems and Information Sciences. Morgan Kaufmann, pp 192–196

12.

Fillmore CJ (1985) Frames and the semantics of understanding. Quaderni di Semant 6(2):222–254

13.

Hu M, Liu B (2004) Mining and summarizing customer reviews. In: Proceedings of the tenth ACM SIGKDD international Conference on Knowledge Discovery and Data Mining. ACM, New York, pp 168–177

14.

Kiritchenko S, Zhu X, Cherry C, Mohammad S (2014) Nrc-canada-2014: Detecting aspects and sentiment in customer reviews. In: Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). Association for Computational Linguistics and Dublin City University, Dublin, Ireland, pp 437–442

15.

Liu B (2012) Sentiment analysis and opinion mining. synthesis lectures on human language technologies. Morgan & Claypool Publishers, USA

16.

Owoputi O, OConnor B, Dyer C, Gimpel K, Schneider N (2012) Part-of-speech tagging for twitter: Word clusters and other advances. School of Computer Science, Carnegie Mellon University, Tech. Rep

17.

Peitek N (2014) Exploration of competitive market behavior using near-real-time sentiment analysis. Master’s thesis, Otto-von-Guericke-University Magdeburg

18.

Pontiki M, Galanis D, Pavlopoulos J, Papageorgiou H, Androutsopoulos I, Manandhar S (2014) Semeval-2014 task 4: Aspect based sentiment analysis. In: Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). Association for Computational Linguistics and Dublin City University, Dublin, Ireland, pp 27–35

19.

Popescu AM, Etzioni O (2007) Extracting product features and opinions from reviews. In: Natural language processing and text mining. Springer, New York, pp 9–28

20.

Poria S, Cambria E, Ku LW, Gui C, Gelbukh A (2014) Proceedings of the Second Workshop on Natural Language Processing for Social Media (SocialNLP), chap. A Rule-Based Approach to Aspect Extraction from Product Reviews. Association for Computational Linguistics and Dublin City University, Dublin, pp 28–37

21.

Ruppenhofer J, Ellsworth M, Petruck MRL, Johnson CR, Scheffczyk J (2005) FrameNet II: Extended theory and practice. Tech. rep, ICSI

22.

Schmidt T (2007) The kicktionary: A multilingual resource of the language of football. In: Rehm G, Witt A, Lemnitzer L (eds) Data structures for linguistic resources and applications. Gunter Narr, Tuebingen, pp 189–196

23.

Thet TT, Na JC, Khoo CSG (2010) Aspect-based sentiment analysis of movie reviews on discussion boards. J Inf Sci 36(6):823–848CrossRef

24.

Toutanova K, Manning CD (2000) Enriching the knowledge sources used in a maximum entropy part-of-speech tagger. In: Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics, vol 13. Association for Computational Linguistics, USA, pp 63–70

25.

Vechtomova O (2009) Book review: Introduction to information retrieval by christopher d. Manning, Prabhakar Raghavan, and Hinrich Schütze. Computational linguistics, vol 35. Cambridge University Press, Cambridge

Titel: AspectFrameNet: a frameNet extension for analysis of sentiments around product aspects
verfasst von: Sanjay Chatterji
Nitish Varshney
Ranjan Kumar Rahul
Publikationsdatum: 13.07.2016
Verlag: Springer US
Erschienen in: The Journal of Supercomputing / Ausgabe 3/2017
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-016-1808-6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 3/2017

Development of an ultra-HD HEVC encoder using SIMD implementation and fast encoding schemes for smart surveillance system

Real-time wireless multisensory smart surveillance with 3D-HEVC streams for internet-of-things (IoT)

Evolutionary Multiobjective Optimization algorithm for multimedia delivery in critical applications through Content-Aware Networks

A novel fruit fly framework for multi-objective shape design of tubular linear synchronous motor

An optimal adaptive stabilizing algorithm for two edge-disjoint paths problem

Moving object detection using modified temporal differencing and local fuzzy thresholding