Classification of means and methods of the Web semantic retrieval

J.V. Rogushina

Abstract


Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability.

In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

Problems in programming 2017; 1: 30-50


Keywords


semantic search, ontology; Semantic Web; personification of retrieval

References


Hendler J. Web 3.0: The dawn of semantic search. Computer, 2010, 43(l). P. 77-80. https://doi.org/10.1109/MC.2010.26

Baeza-Yates R., A. Raghavan R. Next generation Web search // S. Ceri and M. Brambilla, editors, Search Computing, Springer, 2010. P. 11-23. https://doi.org/10.1007/978-3-642-12310-8_2

Lawrence S. Context in the Web Search.

Janowicz K., Wilkes M., Lutz M. Similaritybased information retrieval and its role within spatial data infrastructures. Proc. GIScience-2008, Springer, 2008. P. 151-167. https://doi.org/10.1007/978-3-540-87473-7_10

Broder A. A taxonomy of web search, IBM Research, ACM SIGIR Forum archive, Vol. 36 , Issue 2 (Fall 2002), P. 3-10. https://doi.org/10.1145/792550.792552

Grishanova I.Y. Analitic review of methods and tools of information search for Semantic Web. Problems in programming, 2016. N 1. P. 51-72. [in Ukrainian].

Rogushina J.V. Semantic retrieval for Web on base of ontologies: design of models, tools and methods. Melitopol: Bogdan Hmelnitsky MDUPU , 2015. 291 p. [in Ukrainian].

Gladun A.Y., Rogushina J.V. Semantic technologies: principles and practics. - K.: ADEF-Ukraine, 2016. 308 p. [in Ukrainian]

Brachman R., Schmolze J. An overview of the KL-ONE knowledge representation system. Cognitive Science, 1985, 9(2). https://doi.org/10.1207/s15516709cog0902_1

Bobrow D., Winograd T. An overview of KRL, a knowledge representation language. Cognitive Science 1(1) (1977). https://doi.org/10.1207/s15516709cog0101_2

Antoniou G., Van Harmelen F. Web ontology language: Owl. In Handbook on ontologies. Springer Berlin Heidelberg, 2004. P. 67-92. https://doi.org/10.1007/978-3-540-24750-0_4

Gruber T. A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition. 1993. N 5. P. 199-220. https://doi.org/10.1006/knac.1993.1008

Cyganiak R., Wood D., Lanthaler M.RDF 1. 1 Concepts and Abstract Syntax. W3C Recommendation 25 February 2014.

Rogushina J. Means of the semantic search personification on base of ontological approach. International Journal of Mathematical Sciences and Computing (IJMSC), Vol. 2, N 3. 2016. P. 1-20. https://doi.org/10.5815/ijmsc.2016.03.01

Rogushina J. Use of the Ontological Model for Personification of the Semantic Search. International Journal of Mathematical Sciences and Computing(IJMSC), Vol. 2, N 1, 2016. https://doi.org/10.5815/ijmsc.2016.01.01

Corby O., Dieng-Kuntz R., Faron-Zucker C. Querying the Semantic Web with Corese search engine. Proc. ECAI-2004, IOS Press, 2004. - P. 705-709.

Finin T. W., Ding L., Pan R., Joshi A., Kolari P., Java A., Peng Y. Swoogle: Searching for knowledge on the Semantic Web. Proc. AAAI-2005,. AAAI Press / MIT Press, 2005. P. 1682-1683.

Heflin J., Hendler J. A., Luke S. SHOE: A blueprint for the Semantic Web. D. Fensel, W. Wahlster, and H. Lieberman, editors. Spinning the Semantic Web: Bringing the World Wide Web to Its Full Potential, MIT Press, 2003. P. 29-63.

Kasneci G., Suchanek F.M., Ifrim G., Ramanath M., Weikum G. NAGA: Searching and ranking knowledge. Proc. ICDE-2008, Computer Society, 2008. P. 953-962. https://doi.org/10.1109/ICDE.2008.4497504

Oren E., Gueret C., Schlobach S. Anytime query answering in RDF through evolutionary algorithms. Proc. ISWC- 2008, LNCS 5318, Springer, 2008. P. 98-113. https://doi.org/10.1007/978-3-540-88564-1_7

Buitelaar P., Eigner T., Declerck T. OntoSelect: A dynamic ontology library with support for ontology selection. Proc. Demo Session at ISWC-2004, 2004.

Cheng G., Ge W., Qu Y. Falcons: Searching and browsing entities on the Semantic Web. Proc. WWW-2008, ACM Press, 2008. P. 1101 -1102. https://doi.org/10.1145/1367497.1367676

Harth A., Hogan A., Delbru R., Umbrich J., O'Riain S., Decker S. SWSE: Answers before links. Proc. Semantic Web Challenge 2007, CEUR Workshop Proceedings 295. CEURWS. org, 2007.

Lei Y., Uren V. S., Motta E. SemSearch: A search engine for the Semantic Web. Proc. EKAW-2006, LNCS 4248, Springer, 2006. P. 238-245. https://doi.org/10.1007/11891451_22

Tran T., Cimiano P., Rudolph S., Studer R. Ontology-based interpretation of keywords for semantic search. Proc. ISWC/ASWC-2007, LNCS 4825, Springer, 2007. P. 523-536. https://doi.org/10.1007/978-3-540-76298-0_38

Zenz G., Zhou X., Minack E., Siberski W., Nejdl W. From keywords to semantic queries. Incremental query construction on the Semantic Web. J. Web Sem., 7(3):,2009. P. 166-176. https://doi.org/10.1016/j.websem.2009.07.005

Cimiano P., Haase P., Heizmann J., Mantel M., Studer R.. Towards portable natural language interfaces to knowledge bases - The case of the ORAKEL system. Data Knowl. Eng., 65(2), 2008. P. 325-354. https://doi.org/10.1016/j.datak.2007.10.007

Damljanovic D., Agatonovic M., Cunningham H. Natural language interface to ontologies: Combining syntactic analysis and ontologybased lookup through the user interaction. Proc. ESWC-2010, Part I, LNCS 6088, 2010. P. 106-120. https://doi.org/10.1007/978-3-642-13486-9_8

Fernandez M., Lopez V., Sabou M., Uren V. S., Vallet D., Motta E., Castells P. Semantic search meets the Web. Proc. ICSC-2008, 2008. - P. 253-260. https://doi.org/10.1109/ICSC.2008.52




DOI: https://doi.org/10.15407/pp2017.01.030

Refbacks

  • There are currently no refbacks.