Keiji Shinzato

TSUBAKI: An Open Search Engine Infrastructure for Developing Information Access Methodology

Due to the explosive growth in the amount of information in the last decade, it is getting extremely harder to obtain necessary information by conventional information access methods. Hence, creation of drastically new technology is needed. For developing such new technology, search engine infrastructures are required. Although the existing search engine APIs can be regarded as such infrastructures, these APIs have several restrictions such as a limit on the number of API calls. To help the development of new technology, we are running an open search engine infrastructure, TSUBAKI, on a high-performance computing environment. In this paper, we describe TSUBAKI infrastructure.

Web Information Organization Using Keyword Distillation Based Clustering

This paper describes a system that conducts search result clustering for several thousands of Web pages, and elaborates cluster labels through keyword distillation. Keyword distillation is a method that properly handles spelling variations, transliterations, synonyms, inclusion relations and word ambiguity, using linguistic resources and contexts of a users query. The system provides a clustering result from 1,000 pages in less than one minute by taking advantage of a search engine infrastructure and grid computing environment. Experimental results show that the system correctly merged synonymous keywords and is useful for finding topics hidden in the lower-ranked pages in a search result.

Development of a large-scale web crawler and search engine infrastructure

This paper reports the ongoing development of a large-scale Web crawler and search engine infrastructure at National Institute of Information and Communications Technology. This infrastructure has the following characteristics: (1) It collects one billion Japanese Web pages while keeping them up-to-date. (2) It selects 100 million pages from among the collected pages and converts them into a standard data format to store the results of morphological analysis, dependency parsing, and synonym augmentation. (3) The selected set of pages is searchable and accessible to the users. (4) The scalability of the system is achieved by using a large-scale cluster machine for distributed data processing.