内容紹介

The Web is a gold-mine of data in diverse categories and characteristics, which contains ones that had been hardly available in past, such as a large amount of text in different languages and data from social media. Such data contributes to accelerate progress of research, and at the same time, brings new challenges. In this talk, I introduce our recent research efforts exploiting such novel data on the Web. First, we exploit Twitter data for classifying spiking queries into their topical categories. Spiking queries show sudden spikes in search engines, which represents users' hot attention to them. Therefore, accurate classification of spiking query is important for search engines. Next, I introduce our effort to extract Japanese-English parallel sentence pairs from the Web. We took 3 approaches to mine such data and carefully developed data cleaning framework to extract only high-quality portion. Then I briefly introduce our approach on Japanese-English statistical machine translation.

詳細情報

刊年

2013

形態

電子化映像資料(1時間30分40秒)

シリーズ名

情報科学研究科・ゼミナール講演 ; 平成24年度

注記

講演者所属: Microsoft Research Asia

講演日: 平成25年1月29日

講演場所: 情報科学研究科大講義室L1

標題言語

英語 (eng)

本文言語

英語 (eng)

著者情報

荒瀬, 由紀 (アラセ, ユキ)