A Study on Integration of Bibliographic Information from Multiple Information Sources

本研究旨在开发一个具有多信息源书目信息分析方法、强大的书目匹配功能和高效的信息访问功能的书目信息集成系统。在本研究中，我们取得了以下研究成果。我们建立了一个统计模型来分析各种类型的书目字符串。该模型基于隐马尔可夫模型，能够从参考字符串中提取书目成分。该模型具有描述错误模式字符串的能力，因此它可以应用由OCR获得的参考字符串。实验结果表明，该模型可以对参考文献串进行匹配，匹配精度达到95%左右。(2)开发了一种大型书目数据库检索记录的索引方法。该方法利用数据库中出现频繁的字符串模式，自适应提取变量n-grams。通过该索引，可以有效地合并多个书目数据库。(3)开发了一种分布式自主信息网络中书目数据的采集方法。在该方法中，自治系统通过交换书目元数据来发现包含所需书目信息的引文。该方法利用元数据自适应地改变查询处理路径，实现了自治分布式环境下高效的查询处理机制。

This study aims at developing a bibliographic information integration system which provides with an analysis method for bibliographic information obtained from multiple information sources, robust bibliographic matching function, and efficient information access. In this study, we achieved the following research results.(1)We developed a statistical model for analyzing various kinds of bibliographic strings. The proposed model is based on hidden Markov model and it enables to extract bibliographic components from refer strings. The model has ability to describe error patterns strings, therefore it can be applied reference strings obtained by OCR. We showed that the model can make matching of references strings with the accuracy of about 95% experimentally.(2)We developed an indexing method for searching records from large bibliographic databases. This method uses frequent string patterns appearing in the database and extracts variable n-grams adaptively. By this index, we can merge multiple bibliographic databases efficiently.(3)We developed a method to gather bibliographic data existing in a distributed and autonomous information network. In the proposed method, autonomous systems exchange meta data about bibliographic to discover the cite that holds the desired bibliographic information. In this method, we realized efficient query processing mechanism in autonomous and distributed environment by changing the query processing route adaptively using the meta data.