Abstract
With increasing popularity of the Internet and tremendous amount of on-line text, automatic document classification is important for organizing huge amounts of data. Readers can know the subject of many document fields by reading only some specific Field Association (FA) words. Document fields can be decided efficiently if there are many FA words and if the frequency rate is high. This paper proposes a method for automatically building new FA words. A WWW search engine is used to extract FA word candidates from document corpora. New FA word candidates in each field are automatically compared with previously determined FA words. Then new FA words are appended to an FA word dictionary. From the experiential results, our new system can automatically appended around 44% of new FA words to the existence FA word Dictionary. Moreover, the concentration ratio 0.9 is also effective for extracting relevant FA words that needed for the system design to build FA words automatically.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aoe, J., Morita, K., Mochizuki, H.: An Efficient Retrieval Algorithm of Collocate Information Using Tree Structure. Transaction of The IPSJ 39(9), 2563–2571 (1989)
Atlam, E.-S., Elmarhomy, G., Morita, K., Fuketa, M., Aoe, J.: A New Algorithm for Construction Specific Field Terms Using Co-occurrence Words Information. In: 8th International Conference on Knowledge-Based Intelligent Information & Engineering Systems, Wellington, New Zealand, Part 1, pp. 530–540 (2004)
Atlam, E.-S., Aoe, J.: A new algorithm for automatic extracting FA word candidates from document corpora. The Interim Report of Tokushima University, 25-27 (2004)
Atlam, E.-S., Morita, K., Fuketa, M., Aoe, J.: A New Method for Selecting English Compound Terms and its Knowledge Representation. Information Processing & Management Journal 38(6), 807–821 (2002)
Atlam, E.-S., Fuketa, M., Morita, K., Aoe, J.: Document Similarity measurement using Field association terms. Information Processing & Management 39(6), 809–824 (2003)
Callen, J.P.: Passage and level evidence in document retrieval. In: Proc. of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 302–310 (1994)
Dozawa, T.: Innovative Multi Information Dictionary Imidas 1999. Annual Series. Zueisha Publication Co, Japan (1999) (In Japanese)
Fuhr, N.: Models for retrieval with probabilistic indexing. Information Processing and Retrieval 25(1), 55–72 (1989)
Fukumoto, F., Suzuki, Y.: Automatic Clustering of Articles using Dictionary definitions. In: Proceeding of the 16th International Conference on Computional Linguistic (COLING 1996), pp. 406–411 (1996)
Iwayama, M., Tokunaga, T.: Probabilistic Passage Categorization and Its Application. Journal of Natural language Processing 6(3), 181–198 (1999)
Kawabe, K., Matsumoto, Y.: Acquisition of normal lexical knowledge based on basic level category. Information Processing Society of Japan, SIG note NL125-9, 87–92 (1998)
Melucii, M.: Passage Retrieval and a Probabilistic technique. Information Processing and Management 34(1), 43–68 (1998)
Ohkubo, M., Sugizaki, M., Inoue, T., Tanaka, K.: Extracting Information Demand by Analyzing a WWW Search Login. Trans. of Information Processing Society of Japan 39(7), 2250–2258 (1998)
Salton, G., McGill, M.J.: Introduction of Modern Information Retrieval. McGraw-Hill, New York (1983)
Tsuji, T., Fuketa, M., Morita, K., Aoe, J.: An Efficient Method of Determining FA Terms of Compound Words. Journal of Natural Language Processing 7(2), 3–26 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fuketa, M., Atlam, ES., Ghada, E., Morita, K., Aoe, Ji. (2006). Building New Field Association Term Candidates Automatically by Search Engine. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_42
Download citation
DOI: https://doi.org/10.1007/11893004_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46537-9
Online ISBN: 978-3-540-46539-3
eBook Packages: Computer ScienceComputer Science (R0)