Advanced models and Techniques for Expert Interactive Retrieval Assistance

将在名为CONIT的专家检索助理上完成增强、试验性分析和评估，该助理寻求捕获人类专家搜索者所体现的一些情报并将其正式化。特别是，CONIT协助用户制定正式的问题说明，系统根据该说明在三个不同检索系统的400个数据库中的一个或多个数据库中得出并执行搜索战略。CONIT还协助用户显示文档记录，并根据搜索结果和用户需求重新制定搜索策略。将研究的新辅助技术包括：(1)基于检索匹配标准的估计相关性对文档进行排序；(2)基于对回忆加上时间和成本参数的估计来进行搜索评估的几种方法；以及(3)为当前问题上下文选择最有利的搜索修改策略。有了这些工具，搜索策略规划可以基于更合理、更定量的决策程序，而不是目前检索模式典型的更直观、更定性的程序。对实验进行的分析将考虑特定技术和一般检索模型(归入“智能布尔”一词)实现这些目标的情况。还将通过将CONIT系统从主机环境转换为工作站环境来测试改进的人机界面。

Enhancement, experimental analysis and evalution will be accomplished on an expert retrieval assistant named CONIT which seeks to capture and formalize some of the intelligence embodied in a human expert searcher. In particular CONIT assists users in developing a formalized problem description from which the system derives and executes a search strategy in one or more of 400 databases in three different retrieval systems. CONIT further assists the user in displaying document records and reformulating the search strategy based on search results and user desires. New assistance techniques to be studied include (1) ranking documents by estimated relevance based on retrieval match criteria; (2) several means for search evaluation based on estimates of recall plus time and cost parameters; and (3) selection of the most propitious search modification tactics for the current problem context. With these tools search strategy planning can be based on more rational, quantitative decision- making procedures as opposed to the more intuitive, qualitative procedures typical of current retrieval modalities. Analysis of experiments conducted will consider how well the particular techniques, and general retrieval models (subsumed under the term "smart Boolean"), achieve these goals. An improved human- computer interface will also be tested through conversion of the CONIT system from a mainframe to a workstation environment.