Hits 1.601 – 1.620 of 1.620
| 1601 |
Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies
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In: http://research.ijcaonline.org/volume96/number25/pxc3897048.pdf
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| 1602 |
©ARC Page 29 Holistic Prediction of Student Attrition in Higher Learning Institutions in Malaysia Using Support Vector Machine Model
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In: http://www.arcjournals.org/pdfs/ijrscse/v1-i1/4.pdf
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| 1603 |
Towards Improvements On Domain-Independent Measurements For Collaborative Assessment
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In: http://educationaldatamining.org/EDM2011/wp-content/uploads/proc/edm2011_poster2_Anaya.pdf
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| 1604 |
2011b. Social Context Summarization
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In: http://keg.cs.tsinghua.edu.cn/jietang/publications/SIGIR11-Yang-et-al-social-context-summarization.pdf
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| 1605 |
Performance Analysis of Learning Classifiers for Spoken Digit Under Noisy Conditions
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In: http://www.cisjournal.org/journalofcomputing/archive/vol4no3/vol4no3_6.pdf
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| 1606 |
Relational Concept Discovery in Structured
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In: http://www.iro.umontreal.ca/~valtchev/Papiers/valtchev-et-al-DAM-JIM03.pdf.gz
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| 1607 |
[Extended Abstract] Why Philosophy? Why Now? Engineering Responds to the Crisis of a Creative Era
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In: http://philsci-archive.pitt.edu/4513/1/Why-phil-why-now.pdf
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| 1608 |
In Search of Cinderella: A Transaction Log Analysis of Folktale Searchers
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In: http://www.dongnguyen.nl/publications/trieschnigg-enrich2013.pdf
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| 1609 |
Web Service Programming for Biological Text Mining
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In: http://lair.indiana.edu/sigirbio/final/ghanem.pdf
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| 1610 |
A Less Cumulative Algorithm of Mining Linguistic Browsing Patterns in the World Wide Web
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In: http://www.eusflat.org/publications/proceedings/EUSFLAT_2007/papers/Dyczkowski_Krzysztof_(86).pdf
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| 1611 |
A Hybrid System Using PSO and Data Mining for Determining the Ranking of a New Participant in
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In: http://www.cs.bham.ac.uk/~wbl/biblio/gecco2008/docs/p1713.pdf
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| 1612 |
Mining Entity Translations from Comparable Corpora: A Holistic Graph Mapping Approach
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In: http://www.postech.ac.kr/~swhwang/CIKM11a.pdf
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| 1613 |
FUZZY MINER: EXTRACTING FUZZY RULES FROM NUMERICAL PATTERNS *
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In: http://isl.cs.unipi.gr/db/pubs/journals/ijdwm05.pdf
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| 1614 |
Learning multiple non-redundant codebooks with word clustering for document classification
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| 1615 |
Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach.
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| 1616 |
Comparative text summarization of product reviews
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Abstract:
Master of Science ; Department of Computing and Information Sciences ; William H. Hsu ; This thesis presents an approach towards summarizing product reviews using comparative sentences by sentiment analysis. Specifically, we consider the problem of extracting and scoring features from natural language text for qualitative reviews in a particular domain. When shopping for a product, customers do not find sufficient time to learn about all products on the market. Similarly, manufacturers do not have proper written sources from which to learn about customer opinions. The only available techniques involve gathering customer opinions, often in text form, from e-commerce and social networking web sites and analyzing them, which is a costly and time-consuming process. In this work I address these issues by applying sentiment analysis, an automated method of finding the opinion stated by an author about some entity in a text document. Here I first gather information about smart phones from many e-commerce web sites. I then present a method to differentiate comparative sentences from normal sentences, form feature sets for each domain, and assign a numerical score to each feature of a product and a weight coefficient obtained by statistical machine learning, to be used as a weight for that feature in ranking various products by linear combinations of their weighted feature scores. In this thesis I also explain what role comparative sentences play in summarizing the product. In order to find the polarity of each feature a statistical algorithm is defined using a small-to-medium sized data set. Then I present my experimental environment and results, and conclude with a review of claims and hypotheses stated at the outset. The approach specified in this thesis is evaluated using manual annotated trained data and also using data from domain experts. I also demonstrate empirically how different algorithms on this summarization can be derived from the technique provided by an annotator. Finally, I review diversified options for customers such as providing alternate products for each feature, top features of a product, and overall rankings for products.
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Keyword:
Business Administration; Computer Science (0984); Data Mining; Management (0454); Marketing (0338); Opinion Mining; Sentiment analysis
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URL: http://hdl.handle.net/2097/7031
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| 1617 |
Using data mining to differentiate instruction in college algebra
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| 1618 |
Multi-level mining and visualization of scientific text collections
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| 1620 |
Evaluating behavioral and linguistic changes during drug treatment for depression using tweets in spanish: pairwise comparison study
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