text mining semantic analysis
Báo cáo khoa học: "Extracting a Representation from Text for Semantic Analysis" doc
... fine-grained semantic rep-resentation of text and an approach to con-structing it. This representation is largely extractable by today’s technologies and facili-tates more detailed semantic analysis. ... 2008.c2008 Association for Computational LinguisticsExtracting a Representation from Text for Semantic Analysis Rodney D. Nielsen1,2, Wayne Ward1,2, James H. Martin1, and Martha Palmer1 ... evaluating its impact. 5 Conclusion We presented a novel fine-grained semantic repre-sentation and evaluated it in the context of auto-mated tutoring. A significant contribution of this representation...
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Tapping into the Power of Text Mining
... been specifically designed for text mining or — asa subgroup of text mining methods and a typical application of visualization methods— information retrieval.In text mining or information retrieval ... plain text file. Even though, meanwhile several methods exist that try toexploit also the syntactic structure and semantics of text, most text mining approachesare based on the idea that a text ... extract useful patterns. Text mining refers generally to the process of extracting interesting information and knowledgefrom unstructured text. In this article, we discuss text mining as a young and...
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Text mining power ACM05
... trends for text mining applications appears to involve the integration of data mining and text mining into a single system. The combination of data and text mining is referred to as “duo -mining ... sets up an alert for text mining , s/he will receive several news stories on mining for minerals, and very few that are actually on text mining. Some of the better text mining tools let users ... support. ã hire and train the right IT professionals. Text mining is an evolving field. New text mining techniques are under development and text mining products are being added to the market regularly....
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Tài liệu Báo cáo khoa học: "Prosodic Aids to Syntactic and Semantic Analysis of Spoken English" ppt
... noun modifiers. King races may be a perfect noun group in certain context. 117 Prosodic Aids to Syntactic and Semantic Analysis of Spoken English Chris Rowles and Xiuming Huang AI Systems ... dialogue analysis, and dia- logue management must be used to find the most likely interpretation for the input string. We use pragmatics and knowledge of dialogue struc- ture to find the semantic ... other speaker [for more details, see (Rowles, 1989)]. By determining the dialogue purpose of utteranc- es and their domain context, it is then possible to correct some of the insertion and...
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Tài liệu Báo cáo khoa học: "Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis" ppt
... col-lections (Deerwester et al., 1990), text segmenta-tion (Brants et al., 2002), and text classification(Wu and Gunopulos, 2002).The Probabilistic Latent Semantic Analysis model (PLSA) (Hofmann, 1999) ... in each cluster. We iterated over the109 Improving Probabilistic Latent Semantic Analysis with Principal Component Analysis Ayman FarahatPalo Alto Research Center3333 Coyote Hill RoadPalo ... 94304chen@fxpal.comAbstractProbabilistic Latent Semantic Analysis (PLSA) models have been shown to pro-vide a better model for capturing poly-semy and synonymy than Latent S eman-tic Analysis (LSA). However, the...
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Báo cáo khoa học: "A System for Semantic Analysis of Chemical Compound Names" pdf
... constraintscorresponding to CHEMorph’s semantic repre-sentation output. This is not a trivial task since itrequires to formalize the IUPAC rules of syntaxand semantics of the relevant morphemes. ... Workshop, pages 36–44,Suntec, Singapore, 4 August 2009.c2009 ACL and AFNLPA System for Semantic Analysis of Chemical Compound NamesHenriette EngelkenEML Research gGmbHSchloss-Wolfsbrunnenweg ... tasks of BioNLP. This paper introducesthe architecture of a system for the syntac-tic and semantic analysis of such names.Our system aims at yielding both the de-noted chemical structure and...
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Báo cáo khoa học: " Extending Latent Semantic Analysis with features for dialogue act classification" pot
... IL 60607 USAbdieugen@cs.uic.eduAbstractWe discuss Feature Latent Semantic Analysis (FLSA), an extension to Latent Semantic Analysis (LSA). LSA is a statistical method that is ordinar-ily trained ... dia-logues.1 IntroductionIn this paper, we propose Feature Latent Semantic Analysis (FLSA) as an extension to Latent Seman-tic Analysis (LSA). LSA can be thought as repre-senting the meaning ... Game, to classifyDAs. The drawback of features such as Game is that FLSA: Extending Latent Semantic Analysis with featuresfor dialogue act classificationRiccardo SerafinCEFRIELVia Fucini 220133...
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Báo cáo khoa học: "Semantic Analysis of Japanese Noun Phrases: A New Approach to Dictionary-Based Understanding" doc
... quiring and structuring semantic informa- tion from text. In Proceedings of COLING- A CL '98. Akira Shimazu, Shozo Naito, and Hirosato No- mura. 1987. Semantic structure analysis of Japanese ... analysis (abbreviated to DBA hereafter) for semantic- role relations. 2. Semantic feature-based analysis (abbrevi- ated to SBA hereafter) for some semantic- role relations and all other relations. ... 4 Analysis Method Once we can arrange the diversity of N1 no N 2 senses as in Table 1, their analysis becomes very simple, consisting of the following two modules: 1. Dictionary-based analysis...
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Báo cáo khoa học: "Computing Term Translation Probabilities with Generalized Latent Semantic Analysis" pptx
... offer an advantage for doc-ument classification.2.2 Generalized Latent Semantic Analysis We use the Generalized Latent Semantic Analy-sis (GLSA) (Matveeva et al., 2005) to compute se-mantically ... Thomas K. Lan-dauer, George W. Furnas, and Richard A. Harshman.1990. Indexing b y latent semantic analysis. Jour-nal of the American Society of Information Science,41(6):391–407.Xiaofei ... informa-tion (PMI) as the co-occurrence based measure of semantic associations between pairs of the vocab-ulary terms. PMI has been successfully applied to semantic proximity tests for words (Turney, 2001;Terra...
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Báo cáo khoa học: "A STRUCTURED REPRESENTATION OF WORD-SENSESIR OR SEMANTIC ANALYSIS" pdf
... Understanding system are summarized as follows: Text analysis is performed in four steps: morphologic, morphosyntactic, syntactic and semantic analysis. At each step the results of the preceding ... give a brief overview of the text understanding system and its current status of implementatim~. Figure 1 shows the three modules of the text analyzer. a] The Text Analyzer ~de lalcmn =in. ... combination with the other system components. The semantic processor consists of a semantic knowledge base and a parsing algorithm. The semantic data base presently consists of 850 word-sense...
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Data Mining Association Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 6 Introduction to Data Mining pdf
... Introduction to Data Mining 32 Alternative Methods for Frequent Itemset GenerationTraversal of Itemset Lattice–General-to-specific vs Specific-to-general Data Mining Association Analysis: Basic ... Chapter 6Introduction to Data Mining byTan, Steinbach, Kumarâ Tan,Steinbach, Kumar Introduction to Data Mining 1 © Tan,Steinbach, Kumar Introduction to Data Mining 22 Subset Operation Using ... Data Mining 49 Effect of Support DistributionMany real data sets have skewed support distributionSupport distribution of a retail data set © Tan,Steinbach, Kumar Introduction to Data Mining...
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Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining pot
... Introduction to Data Mining 5 Notion of a Cluster can be AmbiguousHow many clusters?Four Clusters Two Clusters Six Clusters © Tan,Steinbach, Kumar Introduction to Data Mining 41 Limitations ... Kumar Introduction to Data Mining 42 Limitations of K-means: Non-globular ShapesOriginal PointsK-means (2 Clusters) © Tan,Steinbach, Kumar Introduction to Data Mining 13 Types of Clusters: ... Tan,Steinbach, Kumar Introduction to Data Mining 45 Overcoming K-means LimitationsOriginal Points K-means Clusters © Tan,Steinbach, Kumar Introduction to Data Mining 38 Bisecting K-means Example...
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Data Mining Cluster Analysis: Advanced Concepts and Algorithms Lecture Notes for Chapter 9 Introduction to Data Mining pot
... Data Mining 11 Sparsification in the Clustering Process © Tan,Steinbach, Kumar Introduction to Data Mining 22 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data Mining ... DBSCAN) © Tan,Steinbach, Kumar Introduction to Data Mining 18 Experimental Results: CHAMELEON © Tan,Steinbach, Kumar Introduction to Data Mining 16 Chameleon: StepsPreprocessing Step: Represent ... cluster © Tan,Steinbach, Kumar Introduction to Data Mining 23 Experimental Results: CURE (9 clusters) © Tan,Steinbach, Kumar Introduction to Data Mining 26 Creating the SNN GraphSparse GraphLink...
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Báo cáo khoa học: "A Key to Extensible Semantic Analysis" pdf
... " ;Semantic Memory," in Semantic Information Processing. Minsky, M., ed., MIT Press, 1968. 8. Riesbeck, C. and Schank, R. C., "Comprehension by Computer: Expectation-Based Analysis ... Expectation-Based Analysis of Sentences in Context," Tech. report78, Computer Science Department, Yale University, 1976. 20 Metaphor - A Key to Extensible Semantic Analysis Jaime G. Carbonell Carnegie-Mellon ... dictionary. In this paper, I focus on the problem of augmenting the power of a semantic knowledge base used for language analysis by means of metaphorical mappings. The pervasiveness of metaphor...
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Báo cáo khoa học: "On-Line Semantic Analysis of English Texts" ppt
... co- ON-LINE SEMANTIC ANALYSIS OF ENGLISH TEXTS 63 ished when templates have been assigned to the frag- ments of a text. More than one template may still be attached to some text fragment, ... English paragraphs, using a system of semantic analysis programmed in Q32 LISP 1.5. The system of semantic analysis comprises dictionary codings for the text words, coded forms of permitted ... attach semantic frames, the templates, directly to text. I shall describe below (Section 4) a method of fragmenting input texts at the start of an analysis, so as to have a unit of text to...
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