Microsoft Research Asia (Beijing) Intern Report
نویسندگان
چکیده
منابع مشابه
Microsoft Research Asia at the NTCIR-13 STC-2 Task
This paper describes our approaches in NTCIR-13 on short text conversation(STC) task (Chinese). For retrieval-based method, we propose a response matching and ranking model which takes not only the text information into account, but also considers visual features of images corresponding to the text. For generation-based method, we propose the emotion-aware neural response generation model. Base...
متن کاملMicrosoft Research Asia at NTCIR-12 STC Task
This paper describes our approaches at NTCIR-12 short text conversation (STC) task (Chinese). For a new post, instead of considering post-comment similarity, our system focus on finding similar posts in the repository and retrieve their corresponding comments. Meanwhile, we choose frequency property of comments to adjust ranking models. Our best run achieves 0.4854 for mean P, 0.3367 for mean n...
متن کاملMicrosoft Research Asia at the NTCIR-9 Intent Task
In NTCIR-9, we participate in the Intent task, including both the Subtopic Mining subtask and the Document Ranking subtask. In the Subtopic Mining subtask, we mine subtopics from query logs and top results of the queries, and rank them based on their relevance to the query and the similarity between them. In the Document ranking Subtask, we diversify top search results using the mined subtopics...
متن کاملMicrosoft Research Asia at the NTCIR-10 Intent Task
Microsoft Research Asia participated in the Subtopic Mining subtask and Document Ranking subtask of the NTCIR-10 INTENT Task. In the Subtopic Mining subtask, we mine subtopics from query suggestions, clickthrough data and top results of the queries, and rank them based on their importance for the given query. In the Document Ranking subtask, we diversify top search results by estimating the int...
متن کاملMicrosoft Research Asia at the Web Track of TREC 2009
In TREC 2009, we participate in the Web track, and focus on the diversity task. We propose to diversify web search results by first mining subtopics, and then rank results based on mined subtopics. We propose a model to diversify search results by considering both relevance of documents and richness of mined subtopics. Our experimental results show that the model improves diversity of search re...
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ژورنال
عنوان ژورنال: The Journal of The Institute of Image Information and Television Engineers
سال: 2014
ISSN: 1342-6907,1881-6908
DOI: 10.3169/itej.68.155