Intelligent Document Retrieval: Exploiting Markup Structure : 9781402037672

Collections of digital documents can nowadays be found everywhere in institutions, universities or companies. Examples are Web sites or intranets. But searching them for information can still be painful. Searches often return either large numbers of matches or no suitable matches at all. Such document collections can vary a lot in size and how much structure they carry. What they have in common is that they typically do have some structure and that they cover a limited range of topics. The second point is significantly different from documents on the Web in general. The type of search system that we propose in this book can suggest ways of refining or relaxing the query to assist a user in the search process. In order to suggest sensible query modifications we would need to know what the documents are about. Explicit knowledge about the document collection encoded in some electronic form is what we need. However, typically such knowledge is not available. This book describes how that knowledge can be contructed automatically. This book demonstrates how document markup structure can be used to construct domain models for collections of partially structured documents shows how such knowledge can be utilized when searching the document collections presents two implemented search systems which demonstrate the usefulness of this approach.

We are witnessing a massive growth of electronic natural language resources. Most noticeable is the development of the Web, with online newspapers, product catalogues, data archives etc. Millions of users access the Web or other electronic document collections every day. In this book we look at a single aspect of this rather complex area: How can we help a user to navigate a document collection easily, and how can we assist a user who wants to search a collection for documents that satisfy some information need?

We will not look at general Web search, but instead we will concentrate on smaller collections such asWeb sites or collections of classified advertisements. They represent much narrower domains unlike the broad coverage of the Web. One reason for considering this area a worthwhile research issue is the fact that searches in document collections often return either large numbers of matches or no suitable matches at all. We acknowledge that Web search algorithms have matured significantly over the past few years and that a search request submitted to Google1 typically returns excellent matches for a user query. Nevertheless, this is not always the case if the collection is only a fraction the size of the Web and the documents cover a much smaller range of topics. Such collections are very common in institutions, universities or companies.