Abstract
Electronic concept maps, interlinked with other concept maps and multimedia resources, can provide rich knowledge models to capture and share human knowledge. This article presents and evaluates methods to support experts as they extend existing knowledge models, by suggesting new context-relevant topics mined from Web search engines. The task of generating topics to support knowledge model extension raises two research questions: first, how to extract topic descriptors and discriminators from concept maps; and second, how to use these topic descriptors and discriminators to identify candidate topics on the Web with the right balance of novelty and relevance. To address these questions, this article first develops the theoretical framework required for a “topic suggester” to aid information search in the context of a knowledge model under construction. It then presents and evaluates algorithms based on this framework and applied in Extender, an implemented tool for topic suggestion. Extender has been developed and tested within CmapTools, a widely used system for supporting knowledge modeling using concept maps. However, the generality of the algorithms makes them applicable to a broad class of knowledge modeling systems, and to Web search in general.
- Andy Aiken and Derek Sleeman. 2003. Refiner++: A knowledge acquisition and refinement tool. In Proceedings of the KCAP Workshop on Capturing Knowledge from Domain Experts: Progress 8 Prospects (KCAP’03), Derek Sleeman and Yolanda Gil (Eds.). Retrieved from http://www.csd.abdn.ac.uk/∼sleeman/published-papers/p141.pdf.Google Scholar
- Russ B. Altman, Michael Bada, Xiaoqian J. Chai, Michelle Whirl Carillo, Richard O. Chen, and Neil F. Abernethy. 1999. RiboWeb: An ontology-based system for collaborative molecular biology. IEEE Intelligent Systems 14, 5 (1999), 68--76. Google ScholarDigital Library
- Giambattista Amati. 2003. Probability Models for Information Retrieval based on Divergence from Randomness. Ph.D. Dissertation. University of Glasgow.Google Scholar
- Patrick Arnold and Erhard Rahm. 2015. Automatic extraction of semantic relations from Wikipedia. International Journal on Artificial Intelligence Tools 24, 2 (2015), 1540010.Google ScholarCross Ref
- Josianne Basque, Clément Imbeault, Béatrice Pudelko, and Michel Léonard. 2004. Collaborative knowledge modeling between experts and novices: A strategy to support transfer of expertise in an organization. In Concept Maps: Theory, Methodology, Technology. Proceedings of the 1st International Conference on Concept Mapping, A. J. Cañas, J. D. Novak, and F. González (Eds.). Universidad Pública de Navarra, 75--81.Google Scholar
- Jim Blythe, Jihie Kim, Surya Ramachandran, and Yolanda Gil. 2001. An integrated environment for knowledge acquisition. In Proceedings of the 6th International Conference on Intelligent User Interfaces. ACM, 13--20. Google ScholarDigital Library
- Geoffrey Briggs, David Shamma, Alberto Cañas, Roger Carff, Jeffrey Scargle, and Joseph Novak. 2004. Concept maps applied to Mars exploration public outreach. In Concept Maps: Theory, Methodology, Technology. Proceedings of the 1st International Conference on Concept Mapping, A. J. Cañas, J. D. Novak, and F. González (Eds.). Universidad Pública de Navarra, 125--133.Google Scholar
- Jay Budzik, Kristian J. Hammond, and Larry Birnbaum. 2001. Information access in context. Knowledge-Based Systems 14 (2001), 37--53.Google ScholarDigital Library
- Karla L. Caballero Barajas and Ram Akella. 2013. Incorporating statistical topic models in the retrieval of health care documents. In Proceedings of the ShARe/CLEF eHealth Evaluation Lab. ELRA. Retrieved from http://clefpackages.elra.info/clefehealthtask3/workingnotes/CLEFeHealth2013_Lab_ Working_Notes/TASK_3/CLEF2013wn-CLEFeHealth-CaballeroEt2013.pdf.Google Scholar
- Osvaldo Cairó and Silvia Guardati. 2012. The KAMET II methodology: Knowledge acquisition, knowledge modeling and knowledge generation. Expert Systems with Applications 39, 9 (2012), 8108--8114. Google ScholarDigital Library
- Alberto Cañas, David Leake, and Ana Maguitman. 2001. Combining concept mapping with CBR: Experience-based support for knowledge modeling. In Proceedings of the 14th International Florida Artificial Intelligence Research Society Conference. AAAI Press, 286--290. Google ScholarDigital Library
- Alberto J. Cañas, John Coffey, Thomas Reichherzer, Greg Hill, Niranjan Suri, Roger Carff, Tim Mitrovich, and Derek Eberle. 1998. El-tech: A performance support system with embedded training for electronics technicians. In Proceedings of the 11th International Florida Artificial Intelligence Research Society Conference. AAAI Press, 79--83. Google ScholarDigital Library
- Alberto J. Cañas, Greg Hill, Roger Carff, Niranjan Suri, James Lott, Tom Eskridge, Gloria Gómez, Mario Arroyo, and Rodrigo Carvajal. 2004. CmapTools: A knowledge modeling and sharing environment. In Concept Maps: Theory, Methodology, Technology. Proceedings of the 1st International Conference on Concept Mapping, A. J. Cañas, J. D. Novak, and F. González (Eds.). Universidad Pública de Navarra, 125--133.Google Scholar
- Alberto J. Cañas and Joseph D. Novak. 2014. Concept mapping using CmapTools to enhance meaningful learning. In Knowledge Cartography. Springer, 23--45.Google Scholar
- Alberto J. Cañas, Joseph D. Novak, and Jacqueline Vanhear. 2012. Concept Maps: Theory, Methodology, Technology. Proceedings of the 5th International Conference on Concept Mapping. Veritas Press.Google Scholar
- Charles F. Cannell, Peter V. Miller, and Lois Oksenberg. 1981. Research on interviewing techniques. Sociological Methodology 12, 4 (1981), 389--437.Google ScholarCross Ref
- Claudio Carpineto, Stanislaw Osiński, Giovanni Romano, and Dawid Weiss. 2009. A survey of web clustering engines. Computing Surveys 41, 3 (2009), 17. Google ScholarDigital Library
- Claudio Carpineto and Giovanni Romano. 2012. A survey of automatic query expansion in information retrieval. Computing Surveys 44, 1 (2012), 1--50. Google ScholarDigital Library
- Rocío L. Cecchini, Carlos M. Lorenzetti, Ana G. Maguitman, and Filippo Menczer. 2011. A semantic framework for evaluating topical search methods. CLEI Electronic Journal 14, 1 (April 2011). Retrieved from http://www.clei.cl/cleiej/paper.php?id=211.Google ScholarCross Ref
- John Coffey, Thomas Reichherzer, Bernd Owsnicki-Klewe, and Norman Wilde. 2012. Automated concept map generation from services-oriented architecture artifacts. In Concept Maps: Theory, Methodology, Technology. Proceedings of the 5th International Conference on Concept Mapping. University of Malta, Valleta, Malta.Google Scholar
- John W. Coffey. 1999. Institutional Memory Preservation at NASA Glenn Research Center. Unpublished technical report. NASA Glenn Research Center, Cleveland, OH.Google Scholar
- Paulo R. M. Correia, Maria E. I. Malachias, Alberto J. Cañas, and Joseph D. Novak. 2014. Concept Maps: Theory, Methodology, Technology. Proceedings of the 6th International Conference on Concept Mapping. Universidade de Sao Pãulo.Google Scholar
- John Davies, Alistair Duke, and York Sure. 2003. OntoShare: A knowledge management environment for virtual communities of practice. In Proceedings of the International Conference on Knowledge Capture. ACM, 20--27. Google ScholarDigital Library
- Inderjit S. Dhillon. 2001. Co-clustering documents and words using bipartite spectral graph partitioning. In Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM Press, 269--274. Google ScholarDigital Library
- Tom Eskridge and Robert Hoffman. 2012. Ontology creation as a sensemaking activity. IEEE Intelligent Systems 27, 5 (Sep. 2012), 58--65. Google ScholarDigital Library
- Adam Farquhar, Richard Fikes, and James Rice. 1997. The Ontolingua server: A tool for collaborative ontology construction. International Journal of Human-Computer Studies 46, 6 (1997), 707--727. Google ScholarDigital Library
- Paolo Ferragina and Antonio Gulli. 2008. A personalized search engine based on Web-snippet hierarchical clustering. Software: Practice and Experience 38, 2 (2008), 189--225. Google ScholarDigital Library
- Lee A. Freeman and Leonard M. Jessup. 2004. The power and benefits of concept mapping: Measuring use, usefulness, ease of use, and satisfaction. International Journal of Science Education 26 (2004), 151--169.Google ScholarCross Ref
- Ariel Fuxman, Patrick Pantel, Yuanhua Lv, Ashok Chandra, Pradeep Chilakamarri, Michael Gamon, David Hamilton, Bernhard Kohlmeier, Dhyanesh Narayanan, Evangelos Papalexakis, and Bo Zhao. 2014. Contextual insights. In Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion (WWW Companion’14). International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 265--266. Google ScholarDigital Library
- Byron J. Gao, David C. Anastasiu, and Xing Jiang. 2010. Utilizing user-input contextual terms for query disambiguation. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters (COLING’10). Association for Computational Linguistics, Stroudsburg, PA, 329--337. Google ScholarDigital Library
- Alexander Garcia Castro, Philippe Rocca-Serra, Robert Stevens, Chris Taylor, Karim Nashar, Mark Ragan, and Susanna-Assunta Sansone. 2006. The use of concept maps during knowledge elicitation in ontology development processes -- The nutrigenomics use case. BMC Bioinformatics 7, 267 (May 2006), 1--14.Google ScholarCross Ref
- Richard J. Gil and Maria J. Martin-Bautista. 2012. A novel integrated knowledge support system based on ontology learning: Model specification and a case study. Knowledge-Based Systems 36 (2012), 340--352. Google ScholarDigital Library
- Yolanda Gil. 1994. Knowledge refinement in a reflective architecture. In Proceedings of the 12th National Conference on Artificial Intelligence. AAAI Press. Google ScholarDigital Library
- Thomas R. Gruber. 1993. Towards principles for the design of ontologies used for knowledge sharing. In Formal Ontology in Conceptual Analysis and Knowledge Representation, N. Guarino and R. Poli (Eds.). Kluwer Academic Publishers, Deventer, The Netherlands.Google Scholar
- David Gunning, Vinay K. Chaudhri, Peter E. Clark, Ken Barker, Shaw-Yi Chaw, Mark Greaves, Benjamin Grosof, Alice Leung, David D. McDonald, Sunil Mishra, and others. 2010. Project Halo update—Progress toward digital Aristotle. AI Magazine 31, 3 (2010), 33--58.Google ScholarCross Ref
- Frederick Hayes-Roth, Donald A. Waterman, and Douglas B. Lenat. 1983. Building Expert Systems. Addison-Wesley. Google ScholarDigital Library
- Robert R. Hoffman, John W. Coffey, Kenneth M. Ford, and Mary Jo Carnot. 2001. Storm-LK: A human-centered knowledge model for weather forecasting. In Proceedings of the 45th Annual Meeting of the Human Factors and Ergonomics Society.Google ScholarCross Ref
- Katja Hofmann, Anne Schuth, Alejandro Bellogin Kouki, and Maarten de Rijke. 2014. User behavior and bias in click-based recommender evaluation. In Proceedings of European Conference on Information Retrieval (ECIR’14), Lecture Notes in Computer Science. Springer.Google Scholar
- Shang-Hsien Hsieh, Hsien-Tang Lin, Nai-Wen Chi, Kuang-Wu Chou, and Ken-Yu Lin. 2011. Enabling the development of base domain ontology through extraction of knowledge from engineering domain handbooks. Advanced Engineering Informatics 25, 2 (2011), 288--296.Google ScholarCross Ref
- Ellen M. Hufnagel and Christopher Conca. 1994. User response data: The potential for errors and biases. Information Systems Research 5, 1 (1994), 48--73. Google ScholarDigital Library
- Sparck K. Jones. 1972. A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation 28 (1972), 11--21.Google ScholarCross Ref
- Leonard Kaufman and Peter J. Rousseeuw. 1989. Finding Groups in Data: An Introduction to Cluster Analysis. Wiley, New York.Google Scholar
- Reiner Kraft. 2011. Search systems and methods using in-line contextual queries. US Patent 7,958,115.Google Scholar
- Reiner Kraft, Farzin Maghoul, Chi Chao Chang, and Ravi Kumar. 2006. Searching with context. In Proceedings of the 15th International World Wide Web Conference (WWW’15). Google ScholarDigital Library
- David Leake, Ana Maguitman, and Thomas Reichherzer. 2004. Understanding knowledge models: Modeling assessment of concept importance in concept maps. In Proceedings of CogSci-2004.Google Scholar
- David Leake, Ana Maguitman, and Thomas Reichherzer. 2014. Experience-based support for human-centered knowledge modeling. Knowledge-Based Systems 68 (2014), 77--87.Google ScholarDigital Library
- David Leake, Ana Maguitman, Thomas Reichherzer, Alberto Cañas, Marco Carvalho, Marco Arguedas, Sofia Brenes, and Tom Eskridge. 2003. Aiding knowledge capture by searching for extensions of knowledge models. In Proceedings of International Conference on Knowledge Capture (KCAP’03). ACM. Google ScholarDigital Library
- David Leake and David Wilson. 2001. A case-based framework for interactive capture and reuse of design knowledge. Applied Intelligence 14 (2001), 77--94. Google ScholarDigital Library
- Avishay Livne, Vivek Gokuladas, Jaime Teevan, Susan T. Dumais, and Eytan Adar. 2014. CiteSight: Supporting contextual citation recommendation using differential search. In Proceedings of the 37th International ACM SIGIR Conference on Research 8 Development in Information Retrieval (SIGIR’14). ACM, 807--816. Google ScholarDigital Library
- Carlos M. Lorenzetti and Ana G. Maguitman. 2009. A semi-supervised incremental algorithm to automatically formulate topical queries. Information Sciences 179, 12 (2009), 1881--1892. (Including Special Issue on Web Search). Google ScholarDigital Library
- Ana Maguitman, David Leake, Thomas Reichherzer, and Filippo Menczer. 2004. Dynamic extraction of topic descriptors and discriminators: Towards automatic context-based topic search. In Proceedings of the 13th Conference on Information and Knowledge Management (CIKM). ACM, New York, 463--472. Google ScholarDigital Library
- Ana G. Maguitman, Filippo Menczer, Heather Roinestad, and Alessandro Vespignani. 2005. Algorithmic detection of semantic similarity. In Proceedings of the 14th International Conference on World Wide Web (WWW’05). ACM, New York, NY, 107--116. Google ScholarDigital Library
- John W. Mohr and Petko Bogdanov. 2013. Introduction—Topic models: What they are and why they matter. Poetics 41, 6 (2013), 545--569.Google ScholarCross Ref
- Brian M. Moon, Robert R. Hoffman, Joseph D. Novak, and Alberto J. Cañas. 2011. Applied Concept Mapping: Capturing, Analyzing and Organizing Knowledge. CRC Press, New York. Google ScholarDigital Library
- Joseph Novak. 1977. A Theory of Education. Cornell University Press, Ithaca, IL.Google Scholar
- Joseph Novak and Alberto Cañas. 2008. The Theory Underlying Concept Maps and How To Construct Them. Technical Report. Florida Institute for Human and Machine Cognition. Retrieved from http://cmap.ihmc.us/Publications/ResearchPapers/TheoryUnderlyingConceptMaps.pdf.Google Scholar
- Joseph Novak and D. Bob Gowin. 1984. Learning How to Learn. Cambridge University Press.Google Scholar
- Natalya Fridman Noy, Ray W. Fergerson, and Mark A. Musen. 2000. The knowledge model of Protégé-2000: Combining interoperability and flexibility. In Proceedings of European Workshop on Knowledge Acquisition, Modeling and Management (EKAW’00). Google ScholarDigital Library
- Iadh Ounis, Christina Lioma, Craig Macdonald, and Vassilis Plachouras. 2007. Research directions in Terrier: A search engine for advanced retrieval on the web. Novatica/UPGRADE Special Issue on Web Information Access, Ricardo Baeza-Yates et al. (Eds.), Invited Paper VIII, 1 (Feb. 2007), 49--56.Google Scholar
- Cosimo Palmisano, Alexander Tuzhilin, and Michele Gorgoglione. 2008. Using context to improve predictive modeling of customers in personalization applications. IEEE Transactions on Knowledge and Data Engineering 20, 11 (2008), 1535--1549. Google ScholarDigital Library
- Alexander Panchenko, Sergey Adeykin, Alexey Romanov, and Pavel Romanov. 2012. Extraction of semantic relations between concepts with KNN algorithms on Wikipedia. In Concept Discovery in Unstructured Data Workshop (CDUD) of International Conference on Formal Concept Analysis. 78--88.Google Scholar
- Kyung-Wha Park, Byoung-Hee Kim, Tae-Suh Park, and Byoung-Tak Zhang. 2014. Uncovering response biases in recommendation. In Workshops at the 28th AAAI Conference on Artificial Intelligence. Multidisciplinary Workshop on Advances in Preference Handling. AAAI Press.Google Scholar
- Thomas Reichherzer and David Leake. 2006a. Towards automatic support for augmenting concept maps with documents. In Proceedings of the 2nd International Conference on Concept Mapping.Google Scholar
- Thomas Reichherzer and David Leake. 2006b. Understanding the role of structure in concept maps. In Proceedings of the 28th Annual Conference of the Cognitive Science Society. 2004--2009.Google Scholar
- Bradley J. Rhodes and Thad Starner. 1996. The remembrance agent: A continuously running automated information retrieval system. In Proceedings of the 1st International Conference on the Practical Application of Intelligent Agents and Multi Agent Technology (PAAM’96). AAAI Press, 487--495.Google Scholar
- Maria Ruiz-Casado, Enrique Alfonseca, and Pablo Castells. 2005. Automatic extraction of semantic relationships for WordNet by means of pattern learning from Wikipedia. In Natural Language Processing and Information Systems. Springer, 67--79. Google ScholarDigital Library
- Gerard Salton. 1971. The SMART Retrieval System -- Experiments in Automatic Document Processing. Prentice Hall. Google ScholarDigital Library
- Gerard Salton. 1979. Mathematics and information retrieval. Journal of Documentation 35, 1 (1979), 1--29.Google ScholarCross Ref
- Gerard Salton and Michael E. Lesk. 1968. Computer evaluation of indexing and text processing. Journal of the ACM 15, 1 (Jan. 1968), 8--36. Google ScholarDigital Library
- Gerard Salton and Chung-Shu Yang. 1973. On the specification of term values in automatic indexing. Journal of Documentation 29 (1973), 351--372.Google ScholarCross Ref
- Heru Agus Santoso, Su-Cheng Haw, and Ziyad T. Abdul-Mehdi. 2011. Ontology extraction from relational database: Concept hierarchy as background knowledge. Knowledge-Based Systems 24, 3 (2011), 457--464. Google ScholarDigital Library
- Beat A. Schwendimann. 2014. Making sense of knowledge integration maps. In Digital Knowledge Maps in Education. Springer, 17--40.Google Scholar
- Nigel Shadbolt and Paul R. Smart. 2015. Knowledge elicitation: Methods, tools and techniques. In Evaluation of Human Work (4th ed.), John R. Wilson and Sarah Sharples (Eds.). CRC Press.Google Scholar
- Rushdi Shams and Adel Elsayed. 2008. Development of a conceptual structure for a domain-specific corpus. In Proceedings of the 3rd International Conference on Concept Mapping, Tallinn, Estonia 8 Helsinki, Finland, 2008.Google Scholar
- Robin Sibson. 1973. SLINK: An optimally efficient algorithm for the single-link cluster method. Computer Journal 16, 1 (1973), 30--34.Google ScholarCross Ref
- Elena Simperl and Markus Luczak-Rösch. 2014. Collaborative ontology engineering: A survey. The Knowledge Engineering Review 29, 1 (2014), 101--131.Google ScholarCross Ref
- Dallas Snider, John Coffey, Thomas Reichherzer, Norman Wilde, Joe Vandeville, Northrop Grumman, Allison Heinen, and Sarah Pramanik. 2014. Using concept maps to introduce software security assurance cases. CrossTalk 27, 5 (2014), 4--9.Google Scholar
- Qiuxia Song, Jin Liu, Ming Ni, Liang Chen, and Jialiang Shen. 2014. Sorting topic specific web pages based on ontology knowledge. In Proceedings of the 10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP’14). IEEE, 880--883. Google ScholarDigital Library
- Steffen Staaba, Jürgen Angeleb, Stefan Deckera, Michael Erdmanna, Andreas Hothoa, Alexander Maedchea, Hans-Peter Schnurra, Rudi Studera, and York Surea. 2000. AI for the web -- Ontology-based community web portals. In Proceedings of the National Conference on Artificial Intelligence (AAAI’00). MIT Press, Menlo Park. Google ScholarDigital Library
- Fabian M. Suchanek, Gjergji Kasneci, and Gerhard Weikum. 2008. YAGO: A large ontology from Wikipedia and WordNet. Web Semantics: Science, Services and Agents on the World Wide Web 6, 3 (2008), 203--217. Google ScholarDigital Library
- Quan Wang, Jun Xu, Hang Li, and Nick Craswell. 2013. Regularized latent semantic indexing: A new approach to large-scale topic modeling. ACM Transactions on Information Systems 31, 1 (Jan. 2013), 5:1--5:44. Google ScholarDigital Library
- Gerhard Weikum and Martin Theobald. 2010. From information to knowledge: Harvesting entities and relationships from web sources. In Proceedings of the 29th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS’10). ACM, New York, NY, 65--76. Google ScholarDigital Library
- S. K. Michael Wong, Wojciech Ziarko, Vijay V. Raghavan, and P. C. N. Wong. 1987. On modeling of information retrieval concepts in vector spaces. ACM Transactions on Database Systems 12, 2 (Jun. 1987), 299--321. Google ScholarDigital Library
- Clement T. Yu, K. Lam, and Gerard Salton. 1982. Term weighting in information retrieval using the term precision model. Journal of the ACM 29, 1 (Jan. 1982), 152--170. Google ScholarDigital Library
- Oren Zamir and Oren Etzioni. 1999. Grouper: A dynamic clustering interface to web search results. Computer Networks 31, 11--16 (1999), 1361--1374. Google ScholarDigital Library
Index Terms
- Mining for Topics to Suggest Knowledge Model Extensions
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