By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Researchers detail new data in Information Technology. According to news originating from Beijing, People's Republic of China, by VerticalNews correspondents, research stated, "Term proximity is effective for many information retrieval (IR) research fields yet remains unexplored in blogosphere IR. The blogosphere is characterized by large amounts of noise, including incohesive, off-topic content and spam."
Our news journalists obtained a quote from the research from the Chinese Academy of Sciences, "Consequently, the classical bag-of-words unigram IR models are not reliable enough to provide robust and effective retrieval performance. In this article, we propose to boost the blog postretrieval performance by employing term proximity information. We investigate a variety of popular and state-of-the-art proximity-based statistical IR models, including a proximity-based counting model, the Markov random field (MRF) model, and the divergence from randomness (DFR) multinomial model. Extensive experimentation on the standard TREC Blog06 test dataset demonstrates that the introduction of term proximity information is indeed beneficial to retrieval from the blogosphere. Results also indicate the superiority of the unordered bi-gram model with the sequential-dependence phrases over other variants of the proximity-based models. Finally, inspired by the effectiveness of proximity models, we extend our study by exploring the proximity evidence between uery terms and opinionated terms."
According to the news editors, the research concluded: "The consequent opinionated proximity model shows promising performance in the experiments."
For more information on this research see: Utilizing Term Proximity for Blog Post Retrieval. Journal of the American Society for Information Science and Technology, 2013;64(11):2278-2298. Journal of the American Society for Information Science and Technology can be contacted at: Wiley-Blackwell, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - www.wiley.com/; Journal of the American Society for Information Science and Technology - onlinelibrary.wiley.com/journal/10.1002/(ISSN)1532-2890)
The news correspondents report that additional information may be obtained from Z. Ye, Univ Chinese Academy Sci, Sch Comp & Control Engn, Beijing 100190, People's Republic of China. Additional authors for this research include B. He, L.F. Wang and T.J. Luo.
Keywords for this news article include: Asia, Beijing, Information Technology, People's Republic of China
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