Abstract
Entity-oriented search is the search paradigm of organizing and accessing information centered around entities, and their attributes and relationships. This introductory chapter defines what an entity is, identifies prominent contexts for entity-oriented search, presents a number of specific tasks, puts the subject into a historical perspective, and lays the foundations for the rest of the book.
Download chapter PDF
References
Abiteboul, S., Hull, R., Vianu, V. (eds.): Foundations of Databases: The Logical Level. 1st edn. Addison-Wesley Publishing Co. (1995)
Agarwal, G., Kabra, G., Chang, K.C.C.: Towards rich query interpretation: walking back and forth for mining query templates. In: Proceedings of the 19th international conference on World wide web, WWW ’10, pp. 1–10. ACM (2010). doi: 10.1145/1772690.1772692
Balog, K.: Semistructured data search. In: Ferro, N. (ed.) Bridging Between Information Retrieval and Databases, Lecture Notes in Computer Science, vol. 8173, pp. 74–96. Springer (2014). doi: 10.1007/978-3-642-54798-0_4
Bast, H., Buchhold, B., Haussmann, E.: Semantic search on text and knowledge bases. Found. Trends Inf. Retr. 10(2-3), 119–271 (2016). doi: 10.1561/1500000032
Benetka, J.R., Balog, K., Nørvåg, K.: Anticipating information needs based on check-in activity. In: Proceedings of the 10th ACM International Conference on Web Search and Data Mining, WSDM ’17, pp. 41–50. ACM (2017). doi: 10.1145/3018661.3018679
Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American 284(5), 34–43 (2001)
Beynon-Davies, P.: Database Systems. 3rd edn. Palgrave, Basingstoke, UK (2004)
Blanco, R., Mika, P., Vigna, S.: Effective and efficient entity search in RDF data. In: Proceedings of the 10th International Conference on The Semantic Web, ISWC ’11, pp. 83–97. Springer (2011). doi: 10.1007/978-3-642-25073-6_6
Booch, G.: Object Oriented Design with Applications. Benjamin-Cummings Publishing Co., Inc. (1991)
Chakrabarti, S., Kasturi, S., Balakrishnan, B., Ramakrishnan, G., Saraf, R.: Compressed data structures for annotated web search. In: Proceedings of the 21st International Conference on World Wide Web, WWW ’12, pp. 121–130. ACM (2012). doi: 10.1145/2187836.2187854
Chen, P.P.S.: The entity-relationship model–toward a unified view of data. ACM Trans. Database Syst. 1(1), 9–36 (1976). doi: 10.1145/320434.320440
Cheng, T., Chang, K.C.C.: Beyond pages: Supporting efficient, scalable entity search with dual-inversion index. In: Proceedings of the 13th International Conference on Extending Database Technology, EDBT ’10, pp. 15–26. ACM (2010). doi: 10.1145/1739041.1739047
Cheng, T., Yan, X., Chang, K.C.C.: EntityRank: Searching entities directly and holistically. In: Proceedings of the 33rd International Conference on Very Large Data Bases, VLDB ’07, pp. 387–398 (2007)
Christen, P.: A survey of indexing techniques for scalable record linkage and deduplication. IEEE Trans. on Knowl. and Data Eng. 24(9), 1537–1555 (2012). doi: https://doi.org/10.1109/TKDE.2011.127
Cohen, W.W., Hurst, M., Jensen, L.S.: A flexible learning system for wrapping tables and lists in HTML documents. In: Proceedings of the 11th International Conference on World Wide Web, WWW ’02, pp. 232–241. ACM (2002). doi: 10.1145/511446.511477
Elmagarmid, A.K., Ipeirotis, P.G., Verykios, V.S.: Duplicate record detection: A survey. IEEE Trans. on Knowl. and Data Eng. 19(1), 1–16 (2007). doi: https://doi.org/10.1109/TKDE.2007.9
Fetahu, B., Gadiraju, U., Dietze, S.: Improving entity retrieval on structured data. In: In Proceedings of the 14th International Semantic Web Conference. Springer (2015). doi: 10.1007/978-3-319-25007-6_28
Ganti, V., He, Y., Xin, D.: Keyword++: A framework to improve keyword search over entity databases. Proc. VLDB Endow. 3(1-2), 711–722 (2010). doi: 10.14778/1920841.1920932
Guha, R., McCool, R., Miller, E.: Semantic search. In: Proceedings of the 12th International Conference on World Wide Web, WWW ’03, pp. 700–709. ACM (2003). doi: 10.1145/775152.775250
Guo, J., Xu, G., Cheng, X., Li, H.: Named entity recognition in query. In: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’09, pp. 267–274. ACM (2009)
John, T.: What is semantic search and how it works with Google search (2012)
Johnson, M.: How the statistical revolution changes (computational) linguistics. In: Proceedings of the EACL 2009 Workshop on the Interaction Between Linguistics and Computational Linguistics: Virtuous, Vicious or Vacuous?, ILCL ’09, pp. 3–11. Association for Computational Linguistics (2009)
Lin, T., Pantel, P., Gamon, M., Kannan, A., Fuxman, A.: Active objects. In: Proceedings of the 21st international conference on World Wide Web, WWW ’12, pp. 589–598. ACM (2012). doi: 10.1145/2187836.2187916
Liu, T.Y.: Learning to Rank for Information Retrieval. Springer (2011)
Liu, Y., Bai, K., Mitra, P., Giles, C.L.: TableSeer: Automatic table metadata extraction and searching in digital libraries. In: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL ’07, pp. 91–100. ACM (2007). doi: 10.1145/1255175.1255193
Manning, C.D., Raghavan, P., Schütze, H.: Introduction to Information Retrieval. Cambridge University Press (2008)
Pérez-Agüera, J.R., Arroyo, J., Greenberg, J., Iglesias, J.P., Fresno, V.: Using BM25F for semantic search. In: Proceedings of the 3rd International Semantic Search Workshop, SEMSEARCH ’10. ACM (2010). doi: y10.1145/1863879.1863881
Pichai, S.: Google I/O 2016 keynote (2016)
Pinto, D., McCallum, A., Wei, X., Croft, W.B.: Table extraction using conditional random fields. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’03, pp. 235–242. ACM (2003). doi: 10.1145/860435.860479
Piskorski, J., Yangarber, R.: Information extraction: Past, present and future. In: Multi-source, Multilingual Information Extraction and Summarization, pp. 23–49. Springer (2013). doi: 10.1007/978-3-642-28569-1_2
Pound, J., Hudek, A.K., Ilyas, I.F., Weddell, G.: Interpreting keyword queries over web knowledge bases. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management, CIKM ’12, pp. 305–314. ACM (2012). doi: 10.1145/2396761.2396803
Pound, J., Mika, P., Zaragoza, H.: Ad-hoc object retrieval in the web of data. In: Proceedings of the 19th international conference on World wide web, WWW ’10, pp. 771–780. ACM (2010). doi: 10.1145/1772690.1772769
Qian, L., Cafarella, M.J., Jagadish, H.V.: Sample-driven schema mapping. In: Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data, SIGMOD ’12, pp. 73–84. ACM (2012). doi: 10.1145/2213836.2213846
Rosen, G.: Abstract objects. In: Zalta, E.N. (ed.) The Stanford Encyclopedia of Philosophy (Spring 2017 Edition) (2017)
Salton, G.: Automatic Information Organization and Retrieval. McGraw Hill Text (1968)
Sanderson, M.: Test collection based evaluation of information retrieval systems. Found. Trends Inf. Retr. 4(4), 247–375 (2010). doi: 10.1561/1500000009
Sarawagi, S.: Information extraction. Found. Trends databases 1(3), 261–377 (2008). doi: 10.1561/1900000003
Sarkas, N., Paparizos, S., Tsaparas, P.: Structured annotations of web queries. In: Proceedings of the 2010 ACM SIGMOD International Conference on Management of Data, SIGMOD ’10, pp. 771–782. ACM (2010). doi: 10.1145/1807167.1807251
Sawant, U., Chakrabarti, S.: Learning joint query interpretation and response ranking. In: Proceedings of the 22nd International Conference on World Wide Web, WWW ’13, pp. 1099–1109. ACM (2013). doi: 10.1145/2488388.2488484
Weikum, G.: DB & IR: both sides now. In: Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD ’07, pp. 25–30. ACM (2007). doi: 10.1145/1247480.1247484
Yu, J.X., Qin, L., Chang, L.: Keyword search in relational databases: A survey. IEEE Data Eng. Bull. 33(1), 67–78 (2010)
Author information
Authors and Affiliations
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this book are included in the book's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2018 The Editor(s) (if applicable) and the Author(s)
About this chapter
Cite this chapter
Balog, K. (2018). Introduction. In: Entity-Oriented Search. The Information Retrieval Series, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-93935-3_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-93935-3_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93933-9
Online ISBN: 978-3-319-93935-3
eBook Packages: Computer ScienceComputer Science (R0)