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Faceted exploration of RDF/S datasets: a survey

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Abstract

The amounts of available Semantic Web (SW) data (including Linked Open Data) constantly increases. Users would like to browse and explore effectively such information spaces without having to be acquainted with the various vocabularies and query language syntaxes. This paper discusses the work that has been done in the area for the case of RDF/S datasets, with emphasis on session-based interaction schemes for exploratory search. In particular, it surveys the related works according to various aspects, such as assumed user goals, structuring of the underlying information space, generality and configuration requirements, and various (state space-based) features of the navigation structure. Subsequently it introduces a small but concise formal model of the interaction (that captures the core functionalities) which is used as reference model for describing what the existing systems support. Finally the paper describes the evaluation methods that have been used. Overall, the presented analysis aids the understanding and comparison of the various different approaches that have been proposed so far.

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Notes

  1. Note that there is a wide variation regarding the identified tasks in the literature (refer to Li (2009) for an overview). In this survey we focus on a faceted-oriented task analysis approach.

  2. For example, instead of just displaying the number of books of an author on a particular topic, also show the average price of the author’s books.

  3. One could adopt visualization approaches like in Kehrer and Hauser (2013) or techniques that derive overviews, like the top-k diagrams proposed in Fafalios and Tzitzikas (2014), but such works go beyond the scope of this paper.

  4. Since cr3 does not participate to a madeBy property, an alternative approach that one might follow is to add an artificial value, say NonApplicable/Unknown, whose count would equal 1, for informing the user that one element of the focus has no value to the madeBy property.

  5. This kind of transition is called existential selection in Oren et al. (2006).

  6. TriQ (Arenas et al. 2014) is a datalog based QL that offers a general form of recursion, reasoning and navigational capabilities, that incorporates the main RDF QLs.

  7. http://www.openrdf.org/

  8. http://docs.openlinksw.com/virtuoso/

  9. http://www.cs.ox.ac.uk/isg/tools/RDFox/

  10. This “mapping” can be implemented over any web accessible RDF/S dataset by exploiting the SPARQL extension described in Fafalios and Tzitzikas (2015), even if no triplestore or SPARQL endpoint is installed.

  11. Instructions are available at http://docs.openlinksw.com/virtuoso/rdfsparqlrule.html

  12. Measurements performed b Michalis Mountantonakis

  13. http://mql.freebaseapps.com/

  14. https://www.w3.org/Submission/RDQL/

  15. http://sites.wiwiss.fu-berlin.de/suhl/bizer/ng4j/disco/

  16. http://beckr.org/marbles

  17. http://ode.openlinksw.com

  18. http://trec.nist.gov/

  19. http://www.clef-initiative.eu

  20. http://ir.cis.udel.edu/sessions/

  21. http://trec.nist.gov/data/interactive.html

  22. http://www.clef-initiative.eu/track/clefip

References

  • Agrawal, R.H., Gollapudi, S., Halverson, A., & Ieong, S. (2009). Diversifying search results. In Proceedings of the Second ACM International Conference on Web Search and Data Mining (WSDM’09) (pp. 5–14). NY, USA: ACM.

    Chapter  Google Scholar 

  • Allard, P., & Ferré, S. (2008). Dynamic taxonomies for the semantic web. In Proceedings of the 19th International Conference on Database and Expert Systems Application (DEXA).

  • Arenas, M., Cuenca Grau, B., Kharlamov, E., Marciuska, S., & Zheleznyakov, D. (2014). Faceted search over ontology-enhanced RDF data. In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (pp. 939–948): ACM.

  • Arenas, M., Gottlob, G., & Pieris, A. (2014). Expressive languages for querying the semantic web. In Proceedings of the 33rd ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS’14, (Vol. 2014 pp. 14–26). Snowbird, USA.

  • Athanasis, N., Christophides, V., & Kotzinos, D. (2004). Generating on the fly queries for the semantic web: the ICS-FORTH graphical RQL interface (GRQL). In International Semantic Web Conference (ISWC).

  • Azzopardi, L. (2009). Usage based effectiveness measures: monitoring application performance in information retrieval. In CIKM ’09: Proceeding of the 18th ACM Conference on Information and knowledge Management (pp. 631–640). New York, USA: ACM.

    Chapter  Google Scholar 

  • Ben-Yitzhak, O., Golbandi, N., Har’El, N., Lempel, R., Neumann, A., Ofek-Koifman, S., Sheinwald, D., Shekita, E., Sznajder, B., & Yogev, S. (2008). Beyond basic faceted in procs of the intern. In Conference on Web Search and Web Data Mining (WDSM’08) (pp. 33–44).

  • Berners-lee, T., Chen, Y., Chilton, L., Connolly, D., Dhanaraj, R., Hollenbach, J., Lerer, A., & Sheets, D. (2006). Tabulator: exploring and analyzing linked data on the semantic web. In Proceedings of the 3rd International Semantic Web User Interaction Workshop (SWUI06).

  • Bizer, C., Heath, T., & Berners-Lee, T. (2009). Linked data-the story so far. Journal on Semantic Web and Information Systems, 5(3), 1–22.

    Article  Google Scholar 

  • Broder, A. (2002). A taxonomy of web search. SIGIR Forum, 36(2), 3–10.

    Article  MATH  Google Scholar 

  • Brunetti, J.M., Garcia, R., & Auer, S. (2013). From overview to facets and pivoting for interactive exploration of semantic web data. International Journal on Semantic Web and Information Systems, 9(1), 1–20.

    Article  Google Scholar 

  • Carterette, B., Kanoulas, E., & Yilmaz, E. (2012). Evaluating Web retrieval effectiveness. In Web Search Engine Research (pp. 105–137): Emerald Books.

  • Catarci, T., Di Mascio, T., Franconi, E., Santucci, G., & Tessaris, S. (2003). An ontology based visual tool for query formulation support. In On The Move to Meaningful Internet Systems 2003: OTM 2003 Workshops (pp. 32–33). Heidelberg: Springer Berlin.

    Chapter  Google Scholar 

  • Chapelle, O., Ji, S., Liao, C., Velipasaoglu, E., Lai, L., & Wu, S.-L. (2011). Intent-Based diversification of web search results metrics and algorithms. Information Retrieval, 14(6), 572–592.

    Article  Google Scholar 

  • Clarke, C.L.A., Kolla, M., Cormack, G.V., Vechtomova, O., Ashkan, A., Büttcher, S., & MacKinnon, I. (2008). Novelty and diversity in information retrieval evaluation. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’08) (pp. 659–666). NY, USA: ACM.

    Chapter  Google Scholar 

  • Clarkson, E.C., Navathe, S.B., & Foley, J.D. (2009). Generalized formal models for faceted user interfaces. In JCDL ’09: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (pp. 125–134). NY, USA: ACM.

    Chapter  Google Scholar 

  • Cooper, W.S. (1968). Expected search length: a single measure of retrieval effectiveness based on the weak ordering action of retrieval systems. In American Documentation (pp. 30–41).

  • Dakka, W., Ipeirotis, P., & Wood, K.R. (2005). Automatic construction of multifaceted browsing interfaces. In Procs of CIKM’05 (pp. 768–775).

  • Dash, D., Rao, J., Megiddo, N., Ailamaki, A., & Lohman, G. (2008). Dynamic faceted search for discovery-driven analysis. In CIKM ’08: Proceeding of the 17th ACM conference on Information and knowledge management (pp. 3–12).

  • Erling, O., & Mikhailov, I. (2007). RDF support in the virtuoso DBMS. In Proceedings of 1st Conference on Social Semantic Web.

  • Erling, O., & Mikhailov, I. (2009). Faceted views over large-scale linked data. In Proceedings of the WWW2009 Workshop on Linked Data on the Web.

  • Fafalios, P., Kitsos, I., Marketakis, Y., Baldassarre, C., Salampasis, M., & Tzitzikas, Y. (2012). Web searching with entity mining at query time. In Multidisciplinary Information Retrieval (pp. 73–88). Heidelberg: Springer Berlin.

    Chapter  Google Scholar 

  • Fafalios, P., & Tzitzikas, Y. (2013). X-ENS: semantic enrichment of web search results at real-time. In Proceedings of the 36th International ACM SIGIR conference on Research and development in information retrieval (pp. 1089–1090): ACM.

  • Fafalios, P., & Tzitzikas, Y. (2014). Post-analysis of keyword-based search results using entity mining, linked data and link analysis at query time. In 2014 IEEE Eighth International Conference on Semantic Computing (ICSC 2014). California, USA: IEEE.

    Google Scholar 

  • Fafalios, P., & Tzitzikas, Y. (2015). SPARQL-LD: A SPARQL extension for fetching and querying linked data. In The Semantic Web–ISWC 2015 (Posters & Demonstrations Track). Pennsylvania, USA.

  • Ferré, S. (2010). Conceptual navigation in RDF graphs with SPARQL-like queries. Formal Concept Analysis, 193–208.

  • Ferré, S. (2014). Sparklis: a SPARQL endpoint explorer for expressive question answering. In The Semantic Web–ISWC 2014: Springer.

  • Ferro, N., Silvello, G., Keskustalo, A., Abd Pirkola, H., & Järvelin, K. (2015). The twist measure for ir evaluation: taking user’s effort into account. In Journal of the Association for Information Science and Technology (p. 20).

  • Haag, F., Lohmann, S., Bold, S., & Ertl, T. (2014). Visual SPARQL querying based on extended filter/flow graphs. In Proceedings of the 2014 International Working Conference on Advanced Visual Interfaces, AVI ’14 (pp. 305–312). NY, USA: ACM.

    Google Scholar 

  • Hahn, R., Bizer, C., Sahnwaldt, C., Herta, C., Robinson, S., Bürgle, M., Düwiger, H., & Scheel, U. (2010). Faceted wikipedia search. In Business Information Systems, volume 47 of Lecture Notes in Business Information Processing (pp. 1–11).

  • Harth, A. (2009). VisiNav: visual web data search and navigation. In Proceedings of the 20th International Conference on Database and Expert Systems Applications (DEXA ’09).

  • Hearst, M.A. (2008). UIs for faceted navigation: recent advances and remaining open problems. In Workshop on Computer Interaction and Information Retrieval, HCIR’08.

  • Heim, P., Ertl, T., & Ziegler, J. (2010). Facet graphs: complex semantic querying made easy. In The Semantic Web: Research and Applications (pp. 288–302): Springer.

  • Heitmann, B., Kinsella, S., Hayes, C., & Decker, S. (2009). Implementing Semantic Web Applications: Reference Architecture and Challenges. 5th International Workshop on Semantic Web-Enabled Software Engineering.

  • Hildebrand, M., Ossenbruggen, J., & Hardman, L. (2006). /facet: A Browser for Heterogeneous Semantic Web Repositories. In Procs of ISWC ’06.

  • Holi, M., & Hyvönen, E. (2006). Fuzzy view-based semantic search. In ASWC.

  • Hua, W., Song, Y., Wang, H., & Zhou, X. (2013). Identifying users’ topical tasks in web search. In Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, WSDM ’13 (pp. 93–102). NY, USA: ACM.

    Chapter  Google Scholar 

  • Huynh, D. (2010). Nested faceted browsing.

  • Huynh, D., & Karger, D. (2009). Parallax and Companion: Set-based Browsing for the Data Web. (submitted to WWW ’09).

  • Hyvönen, E., Mäkelä, E., Salminen, M., Valo, A., Viljanen, K., Saarela, S., Junnila, M., & Kettula, S. (2005). MUSEUMFINLAND - finnish museums on the semantic web. Journal of Web Semantics, 3(2-3), 224–241.

    Article  Google Scholar 

  • Järvelin, K., & Kekäläinen, J. (2002). Cumulated Gain-Based evaluation of IR techniques. ACM Transactions Information Systems, 20(4), 422–446.

    Article  Google Scholar 

  • Järvelin, K., Price, S.L., Delcambre, L.M.L., & Nielsen, M.L. (2008). Discounted cumulated gain based evaluation of Multiple-Query IR sessions. In ECIR (pp. 4–15).

  • Kanoulas, E., Carterette, B., Clough, P., & Sanderson, M. (2011). Evaluating multi-query sessions. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’11) (pp. 1053–1062).

  • Karvounarakis, G., Alexaki, S., Christophides, V., Plexousakis, D., & Scholl, M. (2002). Rql: a declarative query language for rdf. In Proceedings of the 11th International Conference on World Wide Web (pp. 592–603): ACM.

  • Kashyap, A., Hristidis, V., & Petropoulos, M. (2010). FACeTOR: Cost-driven exploration of faceted query results. In Proceedings of CIKM’10 (pp. 719–728): ACM.

  • Kehrer, J., & Hauser, H. (2013). Visualization and visual analysis of multifaceted scientific data: A survey. IEEE Transactions on Visualization and Computer Graphics, 19(3), 495–513.

    Article  Google Scholar 

  • Khurso, S., & Tjoa, A.M. (2006). Fulfilling the needs of a metadata creator and analyst. In The Past and Future of Information Systems: 1976-2006 and Beyond, (Vol. 214 pp. 177–188). Boston: Springer.

    Chapter  Google Scholar 

  • Kitsos, I., Magoutis, K., & Tzitzikas, Y. (2013). Scalable Entity-based Summarization of Web Search Results using MapReduce. Distributed and Parallel Databases, (pp. 1–42).

  • Kobilarov, G., & Dickinson, I. (2008). Humboldt:Exploring linked data. In Linked Data on the Web Workshop at WWW2008. Beijing, China.

  • Koren, J., Zhang, Y., & Liu, X. (2008). Personalized interactive faceted search. In WWW’08: Procs of the 17th International Conference on World Wide Web (pp. 477–486). NY, USA: ACM.

    Google Scholar 

  • Kules, B., & Capra, R. (2008). Creating exploratory tasks for a faceted search interface. In The Workshop on Computer Interaction and Information Retrieval, HCIR 2008 (pp. 18–21e).

  • Li, C., Yan, N., Roy, S.B., Lisham, L., & Das, G. (2010). Facetedpedia: Dynamic generation of query-dependent faceted interfaces for wikipedia. In WWW (pp. 651–660).

  • Li, Y. (2009). Exploring the relationships between work task and search task in information search. Journal of the American Society for Information Science and Technology, 60(2), 275–291.

    Article  Google Scholar 

  • Lucchese, C., Orlando, S., Perego, R., Silvestri, F., & Tolomei, G. (2011). Identifying task-based sessions in search engine query logs. In Proceedings of the 4th ACM International Conference on Web Search and Data Mining, WSDM ’11 (pp. 277–286). NY, USA: ACM.

    Google Scholar 

  • Magdy, W., & Jones, G.J.F. (2010). PRES: A Score Metric for Evaluating Recall-oriented Information Retrieval Applications. In Proceeding of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010 (pp. 611–618). Geneva, Switzerland.

  • Mäkelä, E., Hyvönen, E., & Saarela, S. (2006). Ontogator - a semantic View-Based search engine service for web applications. In Proceedings of ISWC ’06 (pp. 847–860).

  • Mallea, A., Arenas, M., Hogan, A., & Polleres, A. (2011). On blank nodes. In The Semantic Web–ISWC 2011 (pp. 421–437): Springer.

  • Manolis, N., & Tzitzikas, Y. (2011). Interactive exploration of fuzzy RDF knowledge bases. In Proceedings of ESWC’11.

  • Marchionini, G. (2006). Exploratory search: from finding to understanding. Communications of the ACM, 49(4), 41–46.

    Article  Google Scholar 

  • Mazzieri, M. (2004). A fuzzy RDF semantics to represent trust metadata. In 1st Workshop on Semantic Web Applications and Perspectives (SWAP2004).

  • Ming, J., Jun, Y., Siyu, G., Jiawei, H., Xiaofei, H., Wei Vivian, Z., & Zheng, C. (2011). Learning search tasks in queries and web pages via graph regularization. In Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’11 (pp. 55–64). NY, USA: ACM.

    Google Scholar 

  • Moffat, A., & Zobel, J. (2008). Rank-biased precision for measurement of retrieval effectiveness. ACM Transactions Information Systems, 27(1), 2:1–2:27.

    Article  Google Scholar 

  • O’Brien, H.L., Toms, E.G., Kelloway, E.K., & Kelley, E. (2008). Developing and evaluating a reliable measure of user engagement. Proceedings of the American Society for Information Science and Technology, 45(1), 1–10.

    Article  Google Scholar 

  • Oren, E., Delbru, R., & Decker, S. (2006). Extending faceted navigation for RDF data. In Proceedings of ISWC ’06.

  • Papadakos, P. (2013). Interactive exploration of Multi-Dimensional information spaces with preference support: PhD thesis, University of Crete.

  • Papadakos, P., Kopidaki, S., Armenatzoglou, N., & Tzitzikas, Y. (2009). Exploratory web searching with dynamic taxonomies and results clustering. In ECDL ’09: Proceedings of the 13th European Conference on Digital Libraries.

  • Papadakos, P., Kopidaki, S., Armenatzoglou, N., & Tzitzikas, Y. (2011). On Exploiting Static and Dynamically-mined Metadata for Exploratory Web Searching. Knowledge and Information Systems.

  • Papadakos, P., & Tzitzikas, Y. (2014). Hippalus: Preference-enriched faceted exploration. In EDBT/ICDT Workshops (pp. 167–172).

  • Papadakos, P., & Tzitzikas, Y. (2015). Comparing the Effectiveness of Intentional Preferences versus Preferences over Specific Choices: A User Study. International Journal of Information and Decision Sciences. (to appear).

  • Paulheim, H., & Probst, F. (2010). Interfaces: Ontology-enhanced user a survey. International Journal Semantic Web Information System, 6(2), 36–59.

    Article  Google Scholar 

  • Pietriga, E., Bizer, C., Karger, D., & Lee, R. (2006). Fresnel - A Browser-Independent Presentation Vocabulary for RDF. In Proceedings of the Second International Workshop on Interaction Design and the Semantic Web (pp. 158–171): Springer.

  • Polowinski, J. (2009). Widgets for faceted browsing. In Proceedings of the Symposium on Human Interface 2009 on Conference Universal Access in Human-Computer Interaction. Part I (pp. 601– 610).

  • Qarabaqi, B., & Riedewald, M. (2014). User-driven refinement of imprecise queries. In IEEE 30th International Conference on Data Engineering, Chicago, ICDE 2014, IL, USA March 31 - April 4, 2014 (pp. 916–927).

  • Robertson, S. (2008). A new interpretation of average precision. In Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’08) (pp. 689–690). NY, USA: ACM.

    Chapter  Google Scholar 

  • Robertson, S.E., Kanoulas, E., & Yilmaz, E. (2010). Extending average precision to graded relevance judgments. In Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’10) (pp. 603–610). NY, USA: ACM.

    Chapter  Google Scholar 

  • Roelof, Z., Sigurbjornsson, B., Adapala, R., Garcia Pueyo, L., Katiyar, A., Kurapati, K., Muralidharan, M., Muthu, S., Murdock, V., Ng, A., Ramani, P., Sahai, A., Sathish, S.T., Vasudev, H., & Vuyyuru, U. (2010). Faceted exploration of image search results. In WWW’10: Proceedings of the 19th International Conference on World Wide Web.

  • Rose, D.E., & Levinson, D. (2004). Understanding user goals in web search. In Proceedings of the 13th International Conference on World Wide Web, WWW ’04.

  • Roy, S.B., Wang, H., Das, G., Nambiar, U., & Mohania, M. (2008). Minimum-effort driven dynamic faceted search in structured databases. In Proceedings of CIKM’08 (pp. 13–22).

  • Russell, A., Smart, P.R., Braines, D., & Shadbolt, N.R. (2008). NITELIGHT: A graphical tool for semantic query construction. In Semantic Web User Interaction Workshop (SWUI) (p. 2008).

  • SIMILE: Longwell RDF Browser (2003). http://simile.mit.edu/wiki/Longwell/.

  • SPARQL Query Language for RDF (2008). W3C Candidate recommendation 15.

  • Sacco, G.M. (2004). Efficient implementation of dynamic taxonomies: Technical Report, Univarsity di Torino.

  • Sacco, G.M., & Tzitzikas, Y. (2009). Dynamic Taxonomies and Faceted Search: Theory, Practice, and Experience: Springer.

  • Sacco, G.M., & Tzitzikas, Y. (2009). Dynamic Taxonomies and Faceted Search: Theory, Practise and Experience. ISBN = 978-3-642-02358-3: Springer.

  • Schraefel, M.C., Smith, D.A., Owens, A., Rusell, A., Harris, C., & Wilson, M.L. (2005). The evolving mspace platform: leveraging the semantic web on the trial of the memex. In Proceedings of Hypertext, (Vol. 2005 pp. 174–183).

  • Schuth, A., & Marx, M. (2011). Evaluation methods for rankings of facetvalues for faceted search. In Proceedings of the Second International Conference on Multilingual and Multimodal Information Access Evaluation (CLEF’11) (pp. 131–136). Berlin, Heidelberg: Springer-Verlag.

    Chapter  Google Scholar 

  • Stadler, C., Martin, M., & Auer, S. (2014). Exploring the web of spatial data with facete. 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 (pp. 175–178). Switzerland: Republic and Canton of Geneva.

    Google Scholar 

  • Stefaner, M., Urban, T., & Seefelder, M. (2008). Elastic lists for facet browsing and resource analysis in the enterprise. In Proceedings of the 19th International Conference on Database and Expert Systems Application (DEXA’08) (pp. 397–401).

  • Stolz, A., & Hepp, M. (2015). An adaptive faceted search interface for structured product offers on the web. In Proceedings of the 4th International Workshop on Intelligent Exploration of Semantic Data (IESD 2015), At Bethlehem. Pennsylvania, USA.

  • Strubulis, C., Flouris, G., Tzitzikas, Y., & Doerr, M. (2014). A case study on propagating and updating provenance information using the cidoc crm. International Journal on Digital Libraries, 15(1), 27– 51.

    Article  Google Scholar 

  • Toms, E.G., O’Brien, H.L., Kopak, R.W., & Freund, L. (2005). Searching for relevance in the relevance of search. In CoLIS (pp. 59–78).

  • Tunkelang, D. (2009). Faceted Search: Morgan & Claypool.

  • Tvarožek, M., Barla, M., Frivolt, G., Tomša, M., & Bieliková, M. (2008). Improving semantic search via integrated personalized faceted and visual graph navigation. In SOFSEM, volume 4910 of Lecture Notes in Computer Science (pp. 778–789): Springer.

  • Tzitzikas, Y., Armenatzoglou, N., & Papadakos, P. (2008). FleXplorer: A framework for providing faceted and dynamic taxonomy-based information exploration. In Proceedings of 19th International Conference on Database and Expert Systems Application (DEXA’08) (pp. 392–396).

  • Tzitzikas, Y., Bailly, N., Papadakos, P., Minadakis, N., & Nikitakis, G. (2015). Species identification through preference-enriched faceted search. In Proceedings of the 9th Metadata and Semantics Research Conference (MTSR ’15). Manchester, UK.

  • Tzitzikas, Y., & Papadakos, P. (2012). Interactive exploration of multi-dimensional and hierarchical information spaces with real-time preference elicitation. Fundamenta Informaticae, 20, 1–42.

    MATH  Google Scholar 

  • Wagner, A., Ladwig, G., & Tran, T. (2011). Browsing-Oriented Semantic faceted search. In DEXA (1) (pp. 303–319).

  • White, R.W., Kules, B., Drucker, S.M., & Search, M. C. Schraefel. (2006). Supporting exploratory introduction, special issue, communications of the ACM. Communications of the ACM, 49(4), 36–39.

    Article  Google Scholar 

  • White, R.W., & Roth, R.A. (2009). Exploratory search: beyond the query-response paradigm (synthesis lectures on information concepts, retrieval & services). Morgan and Claypool Publishers, (p. 3).

  • Wildemuth, B.M., & Freund, L. (2012). Assigning search tasks designed to elicit exploratory search behaviors. In Proceedings of the Symposium on Human-Computer Interaction and Information Retrieval, HCIR ’12 (pp. 4:1–4:10). NY, USA: ACM.

    Google Scholar 

  • Wilson, M.L., & Schraefel, M.C. (2007). Bridging the Gap: Using IR models for evaluating exploratory search interfaces. In SIGCHI 2007 Workshop on Exploratory Search and HCI: ACM.

  • Yang, Y., & Lad, A. (2009). Modeling expected utility of multi-session information distillation. In Proceedings of the 2nd Intern. Conf. on Theory of Information Retrieval: Advances in Information Retrieval Theory (ICTIR’09) (pp. 164–175). Berlin, Heidelberg: Springer-Verlag.

    Chapter  Google Scholar 

  • Yee, K., Swearingen, K., Li, K., & Hearst, M. (2003). Faceted metadata for image search and browsing. In Proceedings of the SIGCHI Conference on Human factors in Computing Systems (pp. 401–408).

  • Yilmaz, E., Shokouhi, M., Craswell, N., & Robertson, S. (2010). Expected browsing utility for web search evaluation. In Proceedings of the 19th ACM International Conference on Information and knowledge management (CIKM’10) (pp. 1561–1564).

  • Zhai, C.X., Cohen, W.W., & Lafferty, J. (2003). Beyond independent relevance: methods and evaluation metrics for subtopic retrieval. In Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval (SIGIR’03) (pp. 10–17): ACM.

  • Zhang, J., & Marchionini, G. (2005). Evaluation and evolution of a browse and search interface: relation browser++. In Proceedings of the National Conference on Digital Government Research (DG. ’05): Digital Government Society of North America.

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  1. Computer Science Department, University of Crete, Heraklion, Greece

    Yannis Tzitzikas & Nikos Manolis

  2. Institute of Computer Science, FORTH-ICS, Heraklion, Greece

    Yannis Tzitzikas, Nikos Manolis & Panagiotis Papadakos

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Tzitzikas, Y., Manolis, N. & Papadakos, P. Faceted exploration of RDF/S datasets: a survey. J Intell Inf Syst 48, 329–364 (2017). https://doi.org/10.1007/s10844-016-0413-8

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