A Partial match technique for multi-attribute keys and its text retrieval application

高效地提取关键词是文本检索系统中的一项重要任务。在日语文本中，有许多由某些类型的字符(片假名、汉字等)组成的复合词。文本中的单词之间没有分隔符。因此，从这样的文本中提取关键词需要花费大量的时间。本研究提出了一种从复合关键词中检测关键词的技术，通过引入一组规则来表示关键词构造的多属性条件。用于有限数量模式的串模式匹配机被应用于规则的匹配，并将关键字候选与关于长期和短期单词的信息一起存储。通过理论分析对该方法进行了评价。对34个日文文本文件的模拟结果表明，该算法的性能为19.4ms/KB，与传统方法相比，提取期望关键词的比率有所提高。

Extracting keywords efficiently is an important task in text retrieval systems. In Japanese text, there are many compound words consisting some kinds of characters (Katakana, Kanji, etc.) and the text has no delimiter among words. Therefore, extracting keywords from such a text takes a lot of time. This research presents a technique of detecting keywords from compound keywords by introducing a set of rules, which represents multi-attribute conditions for keywords conctruction. A string pattern matching machine for a finit number of patterns is applied to matching of the rules and storing keyword candidates together with information bout both long term and short term words. The approach is estimated by theoretical analysis. By the simulation results for 34 Japanese text files, it has been that the algorithm presented has performed 19.4ms/KB and that the ratio of extracting expected keywords increase from the traditional approaches.