Abstract
When searching for the interesting content within a specific website, how to describe the initial need by selecting proper keywords is a critical problem. The character-matching search functions of website can hardly meet users’ requirements. Furthermore, building the content of webpages of a specific web-site and the associated rules is uneconomical. This paper, based on the framework of the Lucene engine, applied a semantic ontology, the calculation of the relevance of word entries, and the semantics of keywords to design an intelligent semantic recommendation system with the Jena secondary semantic analysis technique. Subsequently, the expanded keywords were semantically ranked based on the term frequency analysis technique. Meanwhile, the ontology algorithm and their relevance were introduced as the dynamic weight values. Finally, in the text content retrieval process, the search results were ranked based on the previous relevance weights. The experimental results show that the system designed in this paper is not only easy to develop but also capable of expanding users queries and recommending relevant content. Further, the system can improve the precision and recall for website search results.
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References
Aizawa, A.: An information-theoretic perspective of TF-IDF measures. Inf. Process. Manag. 39, 45–65 (2003)
Chang, P.C., Galley, M., Manning, C.D.: Optimizing Chinese word segmentation for machine translation performance. Presented at The Workshop on Statistical Machine Translation, pp. 224–232. Association for Computational Linguistics (2008)
Cong, Y., Chan, Y., Ragan, M.A.: A novel alignment-free method for detection of lateral genetic transfer based on TF-IDF. Sci. Rep. 6, 1–13 (2016)
Corby, O., Dieng-Kuntz, R., Faron-Zucker, C.: Querying the semantic web with corese search engine. Presented at European Conference on Artificial Intelligence, pp. 705–709 (2017)
Fu, Q.: Lucene research and implementation on the vertical search engine application to university library books. J. Taiyuan Normal Univ. 10, 104–107 (2011)
Hendler, J., Lenat, D., Lenat, D., et al.: Very large knowledge bases-architecture vs engineering. Presented at International Joint Conference on Artificial Intelligence, pp. 2033–2036. Morgan Kaufmann Publishers Inc. (1995)
Hsu, Y.Y., Chen, H.Y., Kao, H.Y.: Using a search engine-based mutually reinforcing approach to assess the semantic relatedness of biomedical terms. Plos One 8 (2013). https://doi.org/10.1371/journal.pone.0077868
Kara, S., Alan, O., Sabuncu, O., et al.: An ontology-based retrieval system using semantic indexing. Presented at the IEEE International Conference on Data Engineering Workshops, pp. 197–202 (2012)
Liu, D.F., Fan, X.S.: Study and application of web crawler algorithm based on heritrix. In: Advanced Materials Research, vol. 220, pp. 1069–1072 (2011)
Lombardo, V., Piana, F., Mimmo, D.: Semantics–informed geological maps: conceptual modeling and knowledge encoding. Comput. Geosci. 116, 12–22 (2018)
Mcbride, B.: A semantic web toolkit. IEEE Internet Comput. 6, 55–59 (2002)
Noy, N.F., Sintek, M., Decker, S., et al.: Creating semantic web contents with Protégé-2000. IEEE Intell. Syst. 16, 60–71 (2005)
Yao, Y.: Library resource vertical search engine based on ontology. Presented at International Conference on Smart Grid and Electrical Automation, pp. 672–675. IEEE Computer Society (2017)
Huntley, R., Dimmer, E., Barrell, D., et al.: The gene ontology annotation (GOA) database. Nat. Preceding 10, 429–438 (2009)
Pirro, G., Talia, D.: An approach to ontology map** based on the Lucene search engine library. Presented at IEEE International Workshop on Database and Expert Systems Applications, pp. 407–411 (2007)
Wang, C., Li, S., **ao, H.: Research on Ontology-based arid areas agriculture search engine. J. Agric. Mech. Res. 8, 184–191 (2013)
Reviewer-Lin, D.: Review of WordNet: An Electronic Lexical Database. MIT Press, Ch. 25, pp. 292–296 (1999)
Sun, J., Li, Y., Wan, J.: Design and implementation of the search engine for earthquake based on Heritrix and Lucene. Seismol. Geomagnetic Obs. Res. 37(5), 172–178 (2016)
Ding, Y.H., Yi, K., **ang, R.H.: Design of paper duplicate detection system based on Lucene. Presented at IEEE Wearable Computing Systems, pp. 36–39 (2010)
Acknowledgments
This work was supported partially from Chinese National Natural Science Foundation “Development of Data Sharing Platform of Tibetan Plateau’s Multi-Source Land-Atmosphere System Information” under grant number 91637313; the Special Scientific Research Fund (Major Special Project) for Public Welfare Professions (Meteorology) under the grant number GYHY(QX) 20150600-7.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhang, Z. et al. (2020). Design and Development of an Intelligent Semantic Recommendation System for Websites. In: Zhang, X., Liu, G., Qiu, M., **ang, W., Huang, T. (eds) Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. CloudComp SmartGift 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-48513-9_16
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DOI: https://doi.org/10.1007/978-3-030-48513-9_16
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