What's worse, the boom in handheld devices with small screens suggests that inaccurate search results prove even less acceptable to users than they have to date. Something has to be done to radically improve text search. Multilevel context-sensitivity is crucial to getting excellent results. Despite several decades of research and several years of high-volume Internet search engine use, na ve methods for text retrieval have never been made to work very well. Dealing adequately with the complexities of human discourse requires multiple levels of context-sensitivity that are not available in the traditional paradigm.
Simple methods do at least provide a start on the problem.
What has proved so difficult is getting good precision and recall from the same query. Generate queries based on query words and query templates, which will often vary according to contextual information about the query subjects. These queries will typically either have high precision but probably low to medium recall, or else high recall but imperfect precision. This strategy of successive result-set refinement, which results in excellence both in precision and recall, is only practical in a compound query paradigm. For example, it is difficult to create a query that reliably returns articles on financial news, without also getting a myriad of false hits about products and services that purport to help companies be more profitable, increase sales, etc.