By Zhao Ru, Jun Guo, Weiran Xu (auth.), Hang Li, Ting Liu, Wei-Ying Ma, Tetsuya Sakai, Kam-Fai Wong, Guodong Zhou (eds.)
This ebook constitutes the completely refereed post-conference complaints of the 4th Asia details Retrieval Symposium, AIRS 2008, held in Harbin, China, in might 2008.
The 39 revised complete papers and forty three revised poster papers awarded have been rigorously reviewed and chosen from one hundred forty four submissions. All present concerns in info retrieval are addressed: purposes, platforms, applied sciences and theoretical elements of data retrieval in textual content, audio, photo, video and multi-media info. The papers are equipped in topical sections on IR versions picture retrieval, textual content class, chinese processing, textual content processing, program of IR, computing device studying, taxonomy, IR tools, info extraction, summarization, multimedia, internet IR, and textual content clustering.
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Extra resources for Information Retrieval Technology: 4th Asia Infomation Retrieval Symposium, AIRS 2008, Harbin, China, January 15-18, 2008 Revised Selected Papers
McGraw-Hill, New York (1968) 3. : A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation 28, 11–21 (1972) 4. : Understanding inverse document frequency: on theoretical arguments for IDF. Journal of Documentation 60, 503–520 (2004) 5. : Context-specific frequencies and discriminativeness for the retrieval of structured documents. , Yavlinsky, A. ) ECIR 2006. LNCS, vol. 3936, pp. 579–582. Springer, Heidelberg (2006) 6. : A Comparison of document, sentence and term event spaces.
The retrieval scoring function of Dirichlet-prior smoothing is written by. -H. Na et al. From Eq. (6), Score(Q,D1) > Score(Q,D2). Thus, Dirichlet-prior smoothing belongs to a length-normalized scoring function. Similarly, we can show that Jelinek-Mercer □ smoothing is also length-normalized one. 1 Experimental Setting For evaluation, we used six TREC test collections. Table 1 summarizes the basic information of each test collection. TREC4-AP is the sub-collection of Associated Press in disk 1 and disk 2 for TREC4.
SPCOMPLETE(D): It consists of all possible subsequent words in document D, and equivalently denoted as SPVAR(1,…|D|)(D), where |D| is the length of document. It is a special type of arbitrary passage. Although completely-arbitrary passage is conceptually simple, the number of possible passages in D is 2|D|-1, which is an exponentially increasing function of the length of document. Therefore, it may be intractable to perform the passage retrieval based on completely-arbitrary passages, since we cannot pre-index all possible arbitrary passages, and cannot compare the scores of all possible passages at retrieval time.