Organizing the results of a search facilitates the user in overviewing the information returned. We regard the clustering task as the tasks of making labels for a list of items and we focus on news articles and propose a clustering method that uses named entity extraction.
Clustering the results of a search helps the user to overview the information returned. In this paper, we regard the clustering task as indexing the search results. Here, an index means a structured label list that can makes it easier for the user to comprehend the labels and search results. To realize this goal, we make three proposals. First is to use… (More)
Neurogenesis in the adult dentate gyrus (DG) is considered to be partly involved in the action of mood stabilizers. However, it remains unclear how mood stabilizers affect neural precursor cells in adult DG. We have established a culture system of adult rat DG-derived neural precursor cells (ADP) and have shown that lithium, a mood stabilizer, and… (More)
Tracking user interests over time is important for making accurate recommendations. However, the widely-used time-decay-based approach worsens the sparsity problem because it deemphasizes old item transactions. We introduce two ideas to solve the sparsity problem. First, we divide the users' transactions into epochs i.e. time periods, and identify epochs… (More)
This paper proposes a highly effective geographic information retrieval method. It assesses the extent implied by place names in documents and then emphasizes place names that are highly specific in terms of identifying locations. Furthermore, the method also assesses the proximity between place names and keywords in each document and adjusts the document… (More)
Information needs expressed by using the same query for a search engine might be totally different, whether on week days or weekends, or during the day or at night. For queries having no temporal changes in search intentions, the same search results ranking may be returned regardless of the time, but for those with temporal changes the ranking must be… (More)
Predicting human activities is important for improving recommender systems or analyzing social relationships among users. Those human activities are usually represented as multi-object relationships (e.g. user's tagging activities for items or user's tweeting activities at some locations). Since multi-object relationships are naturally represented as a… (More)