Ontology-based knowledge discovery from unstructured and semi-structured text

............................................................................................................................ i ACKNOWLEDGEMENTS ................................................................................................... iii TABLE OF CONTENTS ....................................................................................................... iv LIST OF FIGURES .............................................................................................................. vii LIST OF TABLES .................................................................................................................. x 1.1 Background .............................................................................................................. 13 1.2 Motivations .............................................................................................................. 14 1.3 Research Questions .................................................................................................. 14 1.4 Research Contributions ............................................................................................ 15 1.5 Thesis Content .......................................................................................................... 17 2.1 Literature Reviews ................................................................................................... 19 2.1.1 Knowledge Acquisition ..................................................................................... 19 2.1.2 Data Mining and Knowledge Discovery in Database ....................................... 21 2.1.3 The KDD Process Model................................................................................... 21 2.1.4 Comparison of the KDD Process Models ......................................................... 24 2.1.5 Problems of Applying the KDD process for Informal Data .............................. 27 2.2 Improvement of Knowledge Discovery Methodology ............................................. 29 2.3 Related Concepts and Techniques ........................................................................... 31 2.3.1 Ontology Development ..................................................................................... 31 2.3.2 Natural Language Processing ............................................................................ 39 2.3.3 N-gram............................................................................................................... 46 2.3.4 Text Mining ....................................................................................................... 48 2.3.5 Closed-domain question answering ................................................................... 54 2.3.6 Evaluation Measures ......................................................................................... 57 3.1 The Main Concept for the On-KDT Modelling ....................................................... 60 3.2 The Variant Lexicon Ontology Development .......................................................... 62 3.2.1 Background ....................................................................................................... 63 3.2.2 Definition of the VL-ontology........................................................................... 65 3.2.3 The use of the VL-ontology .............................................................................. 67 3.2.4 How to implement the VL-ontology ................................................................. 68 3.2.5 Example of the use of the VL-ontology ............................................................ 72 3.2.6 The Experiments of the VL-ontology ................................................................ 73 3.3 The Elaboration of the ON-KDT methodology ....................................................... 75 3.3.1 Understanding of the application domain and defining the problem ................ 75

[1]  Werner Kuhn,et al.  Ontology-based discovery of geographic information services - An application in disaster management , 2006, Comput. Environ. Urban Syst..

[2]  Thomas Mann.  Will Google's Keyword Searching Eliminate the Need for LC Cataloging and Classification? , 2008 .

[3]  N. Mansurov,et al.  Scenario-based Approach to Evolution of Communication Software , .

[4]  Thomas Reinartz,et al.  A Unifying View on Instance Selection , 2002, Data Mining and Knowledge Discovery.

[5]  Hossein Saiedian,et al.  Scenario-based requirements analysis techniques for real-time software systems: a comparative evaluation , 2004, Requirements Engineering.

[6]  Manuel Montes-y-Gómez,et al.  A Text Mining Approach for Definition Question Answering , 2006, FinTAL.

[7]  Shaojie Qiao,et al.  Parallel Sequential Pattern Mining of Massive Trajectory Data , 2010, Int. J. Comput. Intell. Syst..

[8]  Raymond J. Mooney,et al.  Relational Learning of Pattern-Match Rules for Information Extraction , 1999, CoNLL.

[9]  Enrico Motta,et al.  Knowledge Extraction by Using an Ontology Based Annotation Tool , 2001, Semannot@K-CAP 2001.

[10]  Simin Li,et al.  On Removing Ambiguity in Text Understanding , 1998, PACLIC.

[11]  Niels Gottschalk-Mazouz,et al.  Internet and the flow of knowledge: Which ethical and political challenges will we face? , 2013 .

[12]  Inderjit S. Dhillon,et al.  Iterative clustering of high dimensional text data augmented by local search , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[13]  Yinglin Wang,et al.  Extracting Software Functional Requirements from Free Text Documents , 2009, 2009 International Conference on Information and Multimedia Technology.

[14]  Guy W. Mineau,et al.  Beyond TFIDF Weighting for Text Categorization in the Vector Space Model , 2005, IJCAI.

[15]  Nicola Guarino,et al.  Formal Ontology and Information Systems , 1998 .

[16]  Mehran Sahami,et al.  Text Mining: Classification, Clustering, and Applications , 2009 .

[17]  W. Bruce Croft,et al.  Passage retrieval based on language models , 2002, CIKM.

[18]  Jan Rauch,et al.  Ontology-Enhanced Association Mining , 2005, EWMF/KDO.

[19]  Patrick J. Hayes,et al.  Ontology-based knowledge discovery and sharing in bioinformatics and medical informatics: A brief survey , 2010, 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery.

[20]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[21]  Snehasis Mukhopadhyay,et al.  Knowledge Extraction and Extrapolation Using Ancient and Modern Biomedical Literature , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

[22]  Jay F. Nunamaker,et al.  A natural language approach to content-based video indexing and retrieval for interactive e-learning , 2004, IEEE Transactions on Multimedia.

[23]  Carlos H. Caldas,et al.  Management and analysis of unstructured construction data types , 2008, Adv. Eng. Informatics.

[24]  Pericles Loucopoulos,et al.  Relating evolving business rules to software design , 2004, J. Syst. Archit..

[25]  Oren Etzioni,et al.  Strategies for lifelong knowledge extraction from the web , 2007, K-CAP '07.

[26]  Jimmy J. Lin,et al.  What Makes a Good Answer? The Role of Context in Question Answering , 2003, INTERACT.

[27]  Eduard H. Hovy,et al.  The Use of External Knowledge of Factoid QA , 2001, TREC.

[28]  S. C. Johnson.  Hierarchical clustering schemes , 1967, Psychometrika.

[29]  Kentaro Go,et al.  Scenario-Based Task Analysis , 2003 .

[30]  David E. Millard,et al.  Automatic Ontology-Based Knowledge Extraction from Web Documents , 2003, IEEE Intell. Syst..

[31]  Dongwon Lee,et al.  Comparative analysis of six XML schema languages , 2000, SGMD.

[32]  Ingrid Zukerman,et al.  Query expansion and query reduction in document retrieval , 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

[33]  Annie I. Antón,et al.  Scenario support for effective requirements , 2008, Inf. Softw. Technol..

[34]  Steffen Staab,et al.  S-CREAM: Semiautomatic CREAtion of Metadata , 2002, SAAKM@ECAI.

[35]  James Pustejovskya,et al.  Linguistic Knowledge Extraction from Medline: Automatic Construction of an Acronym Database , 2001 .

[36]  Hector G. Ceballos,et al.  A Knowledge-Based Entrepreneurial Approach for Business Intelligence in Strategic Technologies: Bio-Mems , 2005, AMCIS.

[37]  Thomas Reinartz,et al.  CRISP-DM 1.0: Step-by-step data mining guide , 2000 .

[38]  R. Swaminathan,et al.  Epidemiology of cancer of the cervix: global and national perspective. , 2000, Journal of the Indian Medical Association.

[39]  Jakob Uszkoreit,et al.  Large Scale Parallel Document Mining for Machine Translation , 2010, COLING.

[40]  Chris D. Paice.  Method for Evaluation of Stemming Algorithms Based on Error Counting , 1996, J. Am. Soc. Inf. Sci..

[41]  Francis Eng Hock Tay,et al.  Feature Selection for Support Vector Machines , 2000, IDEAL.

[42]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[43]  Alex Alves Freitas,et al.  Automatic Text Summarization Using a Machine Learning Approach , 2002, SBIA.

[44]  Alexander L. Wolf,et al.  Discovering models of software processes from event-based data , 1998, TSEM.

[45]  Lukasz A. Kurgan,et al.  Knowledge discovery approach to automated cardiac SPECT diagnosis , 2001, Artif. Intell. Medicine.

[46]  Hinrich Schütze,et al.  Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.

[47]  Marko Grobelnik,et al.  Text mining as integration of several related research areas: report on KDD's workshop on text mining 2000 , 2000, SKDD.

[48]  Sourav S. Bhowmick,et al.  Sequential Pattern Mining: A Survey , 2003 .

[49]  Sung-Hyon Myaeng,et al.  Procedural Knowledge Extraction on MEDLINE Abstracts , 2011, AMT.

[50]  Mohammad Reza Kangavari,et al.  Information Retrieval: Improving Question Answering Systems by Query Reformulation and Answer Validation , 2008 .

[51]  Boudewijn F. van Dongen,et al.  Process mining: a two-step approach to balance between underfitting and overfitting , 2008, Software & Systems Modeling.

[52]  Karim K. Hirji.  Exploring data mining implementation , 2001, CACM.

[53]  James A. Hendler,et al.  The National Cancer Institute's Thésaurus and Ontology , 2003, J. Web Semant..

[54]  Jimmy J. Lin,et al.  Answering Clinical Questions with Knowledge-Based and Statistical Techniques , 2007, CL.

[55]  W. Bruce Croft,et al.  Passage retrieval based on language models , 2002, CIKM '02.

[56]  Surapant Meknavin,et al.  Feature-based Thai Word Segmentation , 1997 .

[57]  Kenneth Ward Church.  A Stochastic Parts Program and Noun Phrase Parser for Unrestricted Text , 1988, ANLP.

[58]  Yoav Goldberg,et al.  On the Role of Lexical Features in Sequence Labeling , 2009, EMNLP.

[59]  Anita Burgun-Parenthoine,et al.  BioMeKe : an ontology-based biomedical knowledge extraction system devoted to transcriptome analysis , 2003, MIE.

[60]  Ramakrishnan Srikant,et al.  Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.

[61]  Peter Willett,et al.  The Effectiveness of Stemming for Natural-Language Access to Slovene Textual Data , 1992, J. Am. Soc. Inf. Sci..

[62]  Silvia Miksch,et al.  Ontology-Driven Information Systems : Challenges and Requirements , 2007 .

[63]  Emanuele Della Valle,et al.  An Introduction to Information Retrieval , 2013 .

[64]  Thorsten Joachims,et al.  Transductive Inference for Text Classification using Support Vector Machines , 1999, ICML.

[65]  Daniel T. Larose,et al.  Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .

[66]  Young-In Song,et al.  Probabilistic model for definitional question answering , 2006, SIGIR '06.

[67]  Jian Pei,et al.  Mining frequent patterns by pattern-growth: methodology and implications , 2000, SKDD.

[68]  Chung Hee Hwang,et al.  Incompletely and Imprecisely Speaking: Using Dynamic Ontologies for Representing and Retrieving Information , 1999, KRDB.

[69]  Charles L. A. Clarke,et al.  Relevance ranking for one to three term queries , 1997, Inf. Process. Manag..

[70]  Gideon S. Mann,et al.  Analyses for elucidating current question answering technology , 2001, Natural Language Engineering.

[71]  David D. Clark,et al.  A knowledge plane for the internet , 2003, SIGCOMM '03.

[72]  José Palazzo Moreira de Oliveira,et al.  Concept-based knowledge discovery in texts extracted from the Web , 2000, SKDD.

[73]  Donald K. Wedding,et al.  Discovering Knowledge in Data, an Introduction to Data Mining , 2005, Inf. Process. Manag..

[74]  Lukasz Kurgan,et al.  Trends in Data Mining and Knowledge Discovery , 2005 .

[75]  Dieter Fensel,et al.  Knowledge Engineering: Principles and Methods , 1998, Data Knowl. Eng..

[76]  Kalina Bontcheva,et al.  Hierarchical, perceptron-like learning for ontology-based information extraction , 2007, WWW '07.

[77]  Ronald J. Brachman,et al.  The Process of Knowledge Discovery in Databases: A First Sketch , 1994, KDD Workshop.

[78]  Yoram Singer,et al.  Beyond Word N-Grams , 1996, VLC@ACL.

[79]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery in Databases , 1996, AI Mag..

[80]  Javier Segovia,et al.  A Data Mining & Knowledge Discovery Process Model , 2009 .

[81]  Jean-Marc Adamo,et al.  Data Mining for Association Rules and Sequential Patterns , 2000, Springer New York.

[82]  Jane Huffman Hayes,et al.  Text mining for software engineering: how analyst feedback impacts final results , 2005, MSR '05.

[83]  Preetha Annamalai.  Extracting knowledge in the internet age , 2006, ACM-SE 44.

[84]  Wil M. P. van der Aalst,et al.  Process mining: a research agenda , 2004, Comput. Ind..

[85]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[86]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[87]  Bernard Rothenburger,et al.  Ontology Building using Parallel Enumerative Structures , 2010, KEOD.

[88]  Ronen Feldman,et al.  Book Reviews: The Text Mining Handbook: Advanced Approaches to Analyzing Unstructured Data by Ronen Feldman and James Sanger , 2008, CL.

[89]  Jimmy J. Lin,et al.  Quantitative evaluation of passage retrieval algorithms for question answering , 2003, SIGIR.

[90]  Asunción Gómez-Pérez,et al.  A Roadmap to Ontology Specification Languages , 2000, EKAW.

[91]  Chris D. Paice.  An evaluation method for stemming algorithms , 1994, SIGIR '94.

[92]  Andreas Stolcke,et al.  Precise N-Gram Probabilities From Stochastic Context-Free Grammars , 1994, ACL.

[93]  Nuno Seco,et al.  Using Ontologies for Software Development Knowledge Reuse , 2007, EPIA Workshops.

[94]  Joyce Jackson,et al.  Data Mining; A Conceptual Overview , 2002, Commun. Assoc. Inf. Syst..

[95]  Ruey-Shun Chen,et al.  Ontology-Based Knowledge Extraction-A Case Study of Software Development , 2006, Seventh ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'06).

[96]  Alistair Sutcliffe,et al.  Scenario-based requirements analysis , 1998, Requirements Engineering.

[97]  Daryl Pregibon,et al.  A Statistical Perspective on Knowledge Discovery in Databases , 1996, Advances in Knowledge Discovery and Data Mining.

[98]  Dimitris Kanellopoulos,et al.  Data Preprocessing for Supervised Leaning , 2007 .

[99]  Philip S. Yu,et al.  Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.

[100]  Jian Pei,et al.  Constraint-based sequential pattern mining: the pattern-growth methods , 2007, Journal of Intelligent Information Systems.

[101]  Roland H. C. Yap,et al.  Automatic information extraction from web pages , 2001, SIGIR '01.

[102]  Shailey Minocha,et al.  Supporting Scenario-Based Requirements Engineering , 1998, IEEE Trans. Software Eng..

[103]  Yiming Yang,et al.  A Comparative Study on Feature Selection in Text Categorization , 1997, ICML.

[104]  Patrick Heymans,et al.  A reuse-Oriented Approach for the Construction of Scenario Bases Methods , 1997 .

[105]  Colleen E. Crangle,et al.  Text Summarization in Data Mining , 2002, Soft-Ware.

[106]  Usama M. Fayyad,et al.  Knowledge Discovery in Databases: An Overview , 1997, ILP.

[107]  Paola Velardi,et al.  The Usable Ontology: An Environment for Building and Assessing a Domain Ontology , 2002, SEMWEB.

[108]  Miguel A. Andrade-Navarro,et al.  Automatic Extraction of Biological Information from Scientific Text: Protein-Protein Interactions , 1999, ISMB.

[109]  Ralph Weischedel,et al.  PERFORMANCE MEASURES FOR INFORMATION EXTRACTION , 2007 .

[110]  Tunç D. Medeni,et al.  TACIT KNOWLEDGE EXTRACTION FOR SOFTWARE REQUIREMENT SPECIFICATION (SRS): A PROPOSAL OF RESEARCH METHODOLOGY DESIGN AND EXECUTION FOR KNOWLEDGE VISUALIZATION , 2011 .

[111]  Walter Daelemans,et al.  MBT: A Memory-Based Part of Speech Tagger-Generator , 1996, VLC@COLING.

[112]  William R. Hersh,et al.  Evaluation of biomedical text-mining systems: Lessons learned from information retrieval , 2005, Briefings Bioinform..

[113]  Eduard Hovy,et al.  Automated Text Summarization in SUMMARIST , 1997, ACL 1997.

[114]  Robert L. Mercer,et al.  Class-Based n-gram Models of Natural Language , 1992, CL.

[115]  C. Pechsiri,et al.  Agricultural Knowledge Discovery from Semi-Structured Text , 2005 .

[116]  Murali Mani,et al.  Taxonomy of XML schema languages using formal language theory , 2005, TOIT.

[117]  Leila Kosseim,et al.  Improving the Precision of a Closed-Domain Question-Answering System with Semantic Information , 2004, RIAO.

[118]  Hyoil Han,et al.  Survey of semantic annotation platforms , 2005, SAC '05.

[119]  Bernard Mérialdo,et al.  Tagging English Text with a Probabilistic Model , 1994, CL.

[120]  Shichao Zhang,et al.  Association Rule Mining: Models and Algorithms , 2002 .

[121]  Anastasia Karanastasi,et al.  Agent Technology Meets the Semantic Web: Interoperability and Communication Issues , 2010 .

[122]  Charles L. A. Clarke,et al.  Question Answering by Passage Selection (MultiText Experiments for TREC-9) , 2000, TREC.

[123]  MladenicDunja,et al.  Text mining as integration of several related research areas , 2000 .

[124]  Kemal A. Delic,et al.  Enterprise Knowledge Clouds: Next Generation KM Systems? , 2009, 2009 International Conference on Information, Process, and Knowledge Management.

[125]  Claudio Carpineto,et al.  A Survey of Automatic Query Expansion in Information Retrieval , 2012, CSUR.

[126]  Wessel Kraaij,et al.  Viewing stemming as recall enhancement , 1996, SIGIR '96.

[127]  Padhraic Smyth,et al.  Business applications of data mining , 2002, CACM.

[128]  Steffen Staab,et al.  Towards the self-annotating web , 2004, WWW '04.

[129]  Alessandro Vinciarelli.  Noisy Text Categorization , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[130]  Tiffany Barnes,et al.  An integrated scenario management strategy , 1999, Proceedings IEEE International Symposium on Requirements Engineering (Cat. No.PR00188).

[131]  Daniel Amyot,et al.  Generating scenarios from use case map specifications , 2003, Third International Conference on Quality Software, 2003. Proceedings..

[132]  Simon A. Dobson,et al.  Ontology-based models in pervasive computing systems , 2007, The Knowledge Engineering Review.

[133]  James P. Callan,et al.  Passage-level evidence in document retrieval , 1994, SIGIR '94.

[134]  Hsinchun Chen,et al.  Visualization of large category map for Internet browsing , 2003, Decis. Support Syst..

[135]  Donna Harman,et al.  How effective is suffixing , 1991 .

[136]  Daniela Giovanna Calò,et al.  Data Mining and Statistics: what's the connection? , 2009 .

[137]  James Allan,et al.  Approaches to passage retrieval in full text information systems , 1993, SIGIR.

[138]  Daniel S. Weld,et al.  Autonomously semantifying wikipedia , 2007, CIKM '07.

[139]  James J. Cimino,et al.  Automated knowledge extraction from MEDLINE citations , 2000, AMIA.

[140]  Dejing Dou,et al.  Using multiple ontologies in information extraction , 2009, CIKM.

[141]  Atanas Kiryakov,et al.  KIM – a semantic platform for information extraction and retrieval , 2004, Natural Language Engineering.

[142]  Koen Vanhoof,et al.  Research Challenges in Ubiquitous Knowledge Discovery , 2008, Next Generation of Data Mining.

[143]  Andrew McCallum,et al.  A comparison of event models for naive bayes text classification , 1998, AAAI 1998.

[144]  Tsau Young Lin,et al.  Ontology-Based Scalable and Portable Information Extraction System to Extract Biological Knowledge from Huge Collection of Biomedical Web Documents , 2004, IEEE/WIC/ACM International Conference on Web Intelligence (WI'04).

[145]  Deepak Garg,et al.  Semantic Web Mining of Unstructured Data: Challenges and Opportunities , 2011 .

[146]  Malik Yousef,et al.  One-Class SVMs for Document Classification , 2002, J. Mach. Learn. Res..

[147]  Eduard H. Hovy,et al.  Question Answering in Webclopedia , 2000, TREC.

[148]  Christopher D. Manning,et al.  Introduction to Information Retrieval , 2010, J. Assoc. Inf. Sci. Technol..

[149]  Bruce G. Buchanan,et al.  Ontology-guided knowledge discovery in databases , 2001, K-CAP '01.

[150]  Leonard J. Bass,et al.  Scenario-Based Analysis of Software Architecture , 1996, IEEE Softw..

[151]  Tharam S. Dillon,et al.  Thinking PubMed: an Innovative System for Mental Health Domain , 2008, 2008 21st IEEE International Symposium on Computer-Based Medical Systems.

[152]  Lior Rokach,et al.  Introduction to Knowledge Discovery in Databases , 2005, The Data Mining and Knowledge Discovery Handbook.

[153]  Daniel Marcu,et al.  Natural Language Based Reformulation Resource and Wide Exploitation for Question Answering , 2002, TREC.

[154]  Dejing Dou,et al.  Ontology-based information extraction: An introduction and a survey of current approaches , 2010, J. Inf. Sci..

[155]  MusílekPetr,et al.  A survey of Knowledge Discovery and Data Mining process models , 2006 .

[156]  Regine Freitag,et al.  Making Use of Scenarios for Validating Analysis and Design , 1998, IEEE Trans. Software Eng..

[157]  Pavel Hruby.  Role of Domain Ontologies in Software Factories , 2005 .

[158]  Neil A. M. Maiden,et al.  CREWS-SAVRE: Scenarios for Acquiring and Validating Requirements , 1998, Automated Software Engineering.

[159]  P. Willett,et al.  Effectiveness of stemming for Turkish text retrieval , 2000 .

[160]  Periklis Andritsos,et al.  Overview and semantic issues of text mining , 2007, SGMD.

[161]  J. J. Rocchio,et al.  Relevance feedback in information retrieval , 1971 .

[162]  Gregory Piatetsky-Shapiro,et al.  The KDD process for extracting useful knowledge from volumes of data , 1996, CACM.

[163]  Christian Plaunt,et al.  Subtopic structuring for full-length document access , 1993, SIGIR.

[164]  Claudia Diamantini,et al.  Ontology-Driven KDD Process Composition , 2009, IDA.

[165]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[166]  Ramakrishnan Srikant,et al.  Mining Sequential Patterns: Generalizations and Performance Improvements , 1996, EDBT.

[167]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[168]  Hang Li,et al.  Named entity recognition in query , 2009, SIGIR.

[169]  Penelope Sibun,et al.  A Practical Part-of-Speech Tagger , 1992, ANLP.

[170]  Yaochu Jin,et al.  An approach to rule-based knowledge extraction , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[171]  Lee Spector,et al.  Ontology-Based Knowledge Discovery on the World-Wide Web , 1996 .

[172]  Andrzej Kraslawski,et al.  Knowledge discovery method for the identification of solvents for the bio-catalytic reactions , 2005 .

[173]  Lynette Hirschman,et al.  Natural language question answering: the view from here , 2001, Natural Language Engineering.

[174]  Zainab Abu Bakar,et al.  Effectiveness of Stemming and ngrams String Similarity Matching on Malay Documents , 2011 .

[175]  Eric Brill,et al.  A Simple Rule-Based Part of Speech Tagger , 1992, HLT.

[176]  Lin Li,et al.  Improving Short Text Clustering Performance with Keyword Expansion , 2009, ISNN.

[177]  Khalid Iqbal,et al.  Automated Data Mining Techniques: A Critical Literature Review , 2009, 2009 International Conference on Information Management and Engineering.

[178]  Prashant G. Tandale,et al.  Knowledge Management and the Role of Libraries , 2011 .

[179]  Amedeo Napoli,et al.  Ontology-based knowledge discovery in pharmacogenomics. , 2011, Advances in experimental medicine and biology.

[180]  Olusegun Folorunso,et al.  Data mining as a technique for knowledge management in business process redesign , 2005, Inf. Manag. Comput. Security.

[181]  Jim Sinur.  Magic Quadrant for Business Process Management Suites , 2009 .

[182]  Xiang Ji,et al.  Document clustering with prior knowledge , 2006, SIGIR.

[183]  Andrew Zisserman,et al.  Efficient Visual Search of Videos Cast as Text Retrieval , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[184]  Andrew McCallum,et al.  Information extraction from research papers using conditional random fields , 2006, Inf. Process. Manag..

[185]  Mary Beth Rosson,et al.  Scenario-based design , 2002 .

[186]  Anupam Joshi,et al.  Retriever: Improving Web Search Engine Results Using Clustering , 2000 .

[187]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[188]  Donald Hindle,et al.  Acquiring Disambiguation Rules from Text , 1989, ACL.

[189]  Fouzi Harrag,et al.  Comparing Dimension Reduction Techniques for Arabic Text Classification Using BPNN Algorithm , 2010, 2010 First International Conference on Integrated Intelligent Computing.

[190]  Gaurav Pandey,et al.  On Extracting Structured Knowledge from Unstructured Business Documents , 2007 .

[191]  Gregory Piatetsky-Shapiro,et al.  Knowledge Discovery in Databases: An Overview , 1992, AI Mag..

[192]  Yiyu Yao,et al.  Knowledge Retrieval (KR) , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[193]  S. Uchitel,et al.  Monitoring and control in scenario-based requirements analysis , 2005, Proceedings. 27th International Conference on Software Engineering, 2005. ICSE 2005..

[194]  Steven J. DeRose,et al.  Grammatical Category Disambiguation by Statistical Optimization , 1988, CL.

[195]  Susan Brewer,et al.  Information storage and retrieval , 1959, ACM '59.

[196]  Daniel Sánchez,et al.  Text Knowledge Mining: An Alternative to Text Data Mining , 2008, 2008 IEEE International Conference on Data Mining Workshops.