AUTOMATIC BAYESIAN METHODS IN TEXT RETRIEVAL

一种基于贝叶斯方法的新模型已经被 它与矢量有着有趣的联系 模型G.索尔顿理论上的细节 出去理想情况下，文档必须按“真实的”索引 这些真实的物体 多层次系统中的节点称为 特异性网络每个层次结构都是由 特定性运算符和对象树中的结果 从最普通的根开始， 随着向叶子的方向发展，其特异性更强。 填充节点的对象由文本表示 术语或短语。可能有许多表示任何 单一对象。 作为研究此模型的第一步， 在Visual FoxPro中建立了数据库， 包含从每个文档中提取的短语， 一个用于以方便的方式编辑短语。初始 一组短语也被提取出来的测试之一， 我们希望很快就能得到一组人工判断的MEDLINE记录 开始着手编辑这个数据库。此任务 是项目的第一阶段。下一阶段将 包括检查数据库中的所有短语 看看哪对短语是相互关联的， 布景当这一切完成后，我们将有一个新的 我们的目的是为文档建立索引， 研究检索与此索引，看看它是否是免费的 从困扰普通索引的一些模糊性中 以及相关的检索

A new model based on the Bayesian approach has been developed which has interesting connections with the vector models of G. Salton. Theoretical details have been worked out. Ideally documents must be indexed by the "real" objects that they refer to and these real objects become nodes in a system of multiple hierarchies called a specificity network. Each hierarchy is produced by a specificity operator and results in a tree of objects starting at the root with the most general and moving to greater specificity as one progresses towards the leaves. The objects which populate nodes are represented by textual terms or phrases. There may be many representations of any single object. As a first step in investigating this model a relational database has been constructed in Visual FoxPro that will contain the phrases extracted from each document and allow one to edit the phrases in a convenient manner. The initial set of phrases has also been extracted from one of the test sets of humanly judged MEDLINE records and we expect soon to embark on the task of editing this database. This task is the first stage of the project. The next stage will involve the examination of all the phrases in the database to see which pairs of phrases are related to each other in the set. When this has been completed we will have a new kind of indexing for the documents and it is our purpose to study retrieval with this indexing to see if it is free from some of the ambiguities that plague ordinary indexing and its associated retrieval.