Kazutoshi Umemoto

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In this paper, we propose a two-stage system using user's eye movements to accommodate the increasing demands to obtain information from the Web in an efficient way. In the first stage the system estimates a user's search intent as a set of weighted terms extracted based on the user's eye movements while browsing Web pages. Then in the second stage, the(More)
For intrinsically diverse tasks, in which collecting extensive information from different aspects of a topic is required, searchers often have difficulty formulating queries to explore diverse aspects and deciding when to stop searching. With the goal of helping searchers discover unexplored aspects and find the appropriate timing for search stopping in(More)
We describe a framework incorporating several information extraction methods for the NTCIR-10 One Click Access Task. Our framework first classifies a given query into pre-defined query types, and then extracts sentences and key-value pairs which seem relevant to the query. At this time, our framework adjusts the weights of the extraction methods depending(More)
While search engines sometimes return different documents containing contradictory answers, little is known about how users handle inconsistent information. This paper investigates the effect of <i>search expertise</i> (defined as specialized knowledge on the internal workings of search engines) on search behavior and satisfaction criteria of users. We(More)
This paper proposes a method to discover how a user's search intent changes using his/her behavior during a Web search. A Web search user has a particular search intent and formulates search queries according to that intent. It is, however, a difficult task for the user to formulate a <i>optimal</i> query, a single query able to find documents which(More)
In this paper we address the difficulty of clipping articles from mobile apps. We propose a service called UniClip that allows a user to save the full content of an article by snapping a screenshot part of it. UniClip leverages a huge amount of indexed web data to mine the article by starting with a snapped screenshot. We propose approaches to solve three(More)
To address the difficulty in clipping articles from various mobile applications (apps), we propose a novel framework called UniClip, which allows a user to snap a screen of an article to save the whole article in one place. The key task of the framework is <i>search by screenshots</i>, which has three challenges: (1) how to represent a screenshot; (2) how(More)
This paper proposes a query classification system for a one-click search system that uses feature vectors based on snippet similarity. The proposed system targets the NTCIR-10 1CLICK-2 query classification subtask and classifies queries in Japanese and English into eight predefined classes by using support vector machines (SVMs). In the NTCIR-9 and NTCIR-10(More)
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