Abstract
The scale of the Internet has become vast in the aspect of information. information. And, the performance of internet information retrieval systems are advanced. Now, researches of IIR (Internet Information Retrieval)systems are analysis of means of webpage based on keyword search. Recently, IIR system’s issue is system of searching necessary information for user. In this paper, we propose which search webpage of food related information and servicing the IIR system. Our system shows good performance than Commercial IIR services. We expect our system will be use-full IIR system.
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References
Akiko, A.: An information-theoretic perspective of tf—idf measures. Information Processing and Management: an International Journal 39(1), 45–65 (2003)
Carlo, A., Alberto, R.: Generalized thermodynamics underlying the laws of Zipf and Benford. In: Zhou, J. (ed.) Complex 2009. LNICST, vol. 5, pp. 2232–2237. Springer, Heidelberg (2009)
Fabio, C.: Spoken query processing for interactive information retrieval. Data & Knowledge Engineering 41, 105–124 (2002)
Pereira, F., Naftali, T., Lillian, L.: Distributional clustering of English words. In: Proceedings of the 31st Annual Meeting of the ACL, pp. 183–190 (1993)
Anette, H., Jussi, K., Anna, J.: Automatic Keyword Extraction Using Domain Knowledge. In: Gelbukh, A. (ed.) CICLing 2001. LNCS, vol. 2004, pp. 472–482. Springer, Heidelberg (2001)
Donald, M.: Generalized Inverse Document Frequency. In: Conference on Information and Knowledge Management, pp. 399–408 (2008)
Yataka, M., Mitsuru, I.: Keyword Extraction from a Single Document using Word Co-occurrence Statistical Information. International Journal on artificial Intelligence Tool 13(1), 157–169 (2004)
Thomas, R.: A frequency-based and a Poisson-based definition of the probability of being informative. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 227–234 (2003)
Charles, S.: Dictionary of food: International Food and Cooking Terms from A to Z, 2nd edn. A&C Black Publishers Ltd. (2005)
Nobuyoshi, S., Minoru, U., Yoshifumi, S., Hideki, M.: Fresh Information Retrieval using Cooperative Meta Search Engines. In: Proceedings of the 16th International Conference on Information Networking (ICOIN-16), vol. 2, 7A-2, pp. 1–7 (2002)
O’Meara, T., Patel, A.: A topic-specific Web robot model based on restless bandits. IEEE Internet Computing 5(2), 27–35 (2001)
Wim, V.: Agriculture and the food industry in the information age. European Review of Agricultural Economics 32(3), 347–368 (2005)
food network, http://www.foodnetwork.com/
food 2, http://www.food2.com/
CLucene Project web page, http://clucene.sourceforge.net/
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Pyun, G., Yun, U. (2011). Efficient Food Retrieval Techniques Considering Relative Frequencies of Food Related Words. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Lecture Notes in Computer Science, vol 6935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24082-9_45
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DOI: https://doi.org/10.1007/978-3-642-24082-9_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24081-2
Online ISBN: 978-3-642-24082-9
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