Abstract
The large-scale unordered sentences are springing up on the web since the massive novel web social Medias have emerged. Although those unordered sentences have rich information, they only provide users with incoherent information service because they have loose semantic relations. Users usually expect to obtain semantic coherent information service when they are facing massive unordered sentences. Unfortunately, general web search engines are not applicable to such issue, because they only return a flat list of unordered web pages based on keywords. In this paper, we propose a novel semantic coherence based intelligent search system. The search system can provide semantic coherence based search service, which includes choosing semantic coherent sentences and ranking the sentences by a semantic coherent way. When a user enters some semantic incoherent sentences as queries, our system can return a semantic coherent paragraph as search results. The process is demonstrated by a prototypical system and experiments are conducted to validate its correctness. The results of experiments have shown that the system can distinguish semantic coherent sentences from others and rank the sentences by a semantic coherent way with higher accuracy.
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References
de Beaugrande, R., Dressler, W.: Introduction to text linguistics (1981)
Graesser, A.C., Singer, M., Trabasso, T.: Constructing inferences during narrative text comprehension. Psychological Review 101(3), 371 (1994)
Sullivan, D.: How search engines work. Search Engine Watch 14 (2002)
Zhang, J., Cheung, C.: Meta-search-engine feature analysis. Online Information Review 27(6), 433–441 (2003)
Kasneci, G., Suchanek, F.M., Ifrim, G., Ramanath, M., Weikum, G.: Naga: Searching and ranking knowledge. In: IEEE 24th International Conference on Data Engineering, ICDE 2008, pp. 953–962 (2008)
Sudeepthi, G., Anuradha, G., Babu, M.S.P.: A Survey on Semantic Web Search Engine. International Journal of Computer Science 9 (2012)
Dietze, H., Schroeder, M.: GoWeb: a semantic search engine for the life science web. BMC Bioinformatics 10(suppl. 10), S7 (2009)
Lee, D., Kwon, J., Yang, S., Lee, S.: Improvement of the Recall and the Precision for Semantic Web Services Search. In: 6th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2007, pp. 763–768 (2007)
Luo, X., Xu, Z., Yu, J., Chen, X.: Building association link network for semantic link on web resources. IEEE Transactions on Automation Science and Engineering 8(3), 482–494 (2011)
Luo, X., Cai, C., Hu, Q.: Text knowledge representation model based on human concept learning. In: 2010 9th IEEE International Conference on Cognitive Informatics (ICCI), pp. 383–390 (2010)
Luo, X., Yu, J., Li, Q., Liu, F., Xu, Z.: Building web knowledge flows based on interactive computing with semantics. New Generation Computing 28(2), 113–120 (2010)
Meng, D., Huang, X.: An Interactive Intelligent Search Engine Model Research Based on User Information Preference. In: 9th International Conference on Computer Science and Informatics (2006)
Prakash, K.S.S., Raghavan, S.: Intelligent Search Engine: Simulation to Implementation. In: Proceedings of the iiWAS 2004, The Sixth International Conference on Information Integration and Web-based Applications Services, September 27-29 (2004)
Inamdar, S., Shinde, G.: An Agent Based Intelligent Search Engine System for Web mining.Research. Reflections and Innovations in Integrating ICT in Education (2008)
Collins, A.M., Loftus, E.F.: A spreading-activation theory of semantic processing. Psychological Review 82(6), 407–428 (1975)
Matsui, T.: Experimenstal pragmatics: Towards testing relevance-based predictions about anaphoric bridging inferences. Springer (2001)
Joachims, T.: Optimizing search engines using clickthrough data. In: Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 133–142 (2002)
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Liu, W., Luo, X. (2013). A Semantic Coherence Based Intelligent Search System. In: Yoshida, T., Kou, G., Skowron, A., Cao, J., Hacid, H., Zhong, N. (eds) Active Media Technology. AMT 2013. Lecture Notes in Computer Science, vol 8210. Springer, Cham. https://doi.org/10.1007/978-3-319-02750-0_42
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DOI: https://doi.org/10.1007/978-3-319-02750-0_42
Publisher Name: Springer, Cham
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