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Identifying Tips Web Sites of a Specific Query based on Search Engine Suggests and the Topic Distribution.

, , , , , , and . IEEE BigData, page 4360-4366. IEEE, (2018)

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Collecting and Analyzing Japanese Splogs based on Characteristics of Keywords., , , , , , and . ICWSM, The AAAI Press, (2008)Analyzing Time Series Changes of Correlation between Market Share and Concerns on Companies measured through Search Engine Suggests., , , , , , , and . LREC, European Language Resources Association (ELRA), (2016)Cross-Lingual Analysis of Concerns and Reports on Crimes in Blogs., , , , , , , , and . UCMedia, volume 40 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 315-320. Springer, (2009)An Empirical Study on Optimal Correlation between Market Share and Concerns on Companies Measured through Search Engine Suggests., , , , , and . AINA Workshops, page 214-219. IEEE Computer Society, (2016)Overviewing the Knowledge of a Query Keyword by Clustering Viewpoints of Web Search Information Needs., , , , , and . AINA Workshops, page 535-540. IEEE Computer Society, (2015)Selecting Web Search Results of Diverse Contents with Search Engine Suggests and a Topic Model., , , , , and . AINA Workshops, page 455-460. IEEE Computer Society, (2016)Measuring Beginner Friendliness of Japanese Web Pages explaining Academic Concepts by Integrating Neural Image Feature and Text Features., , , , , , and . NLP-TEA@ACL, page 143-151. Association for Computational Linguistics, (2018)MRC Examples Answerable by BERT without a Question Are Less Effective in MRC Model Training., , , , and . AACL/IJCNLP (Student Research Workshop), page 146-152. Association for Computational Linguistics, (2020)Detecting splogs using similarities of splog HTML structures., , , , and . ICUIMC, page 37. ACM, (2010)BERT based Web Mining of Concerns and Reviews for TV Drama Audience., , , , , , , and . WI (Companion), page 64-71. ACM, (2019)