An Analysis of Statistical and Syntactic Phrases

As the amount of textual information available through the World Wide Web grows, there is a growing need for high-precision IR systems that enable a user to nd useful information from the masses of available textual data. Phrases have traditionally been regarded as precision-enhancing devices and have proved useful as content-identi ers in representing documents. In this study, we compare the usefulness of phrases recognized using linguistic methods and those recognized by statistical techniques. We focus in particular on high-precision retrieval. We discover that once a good basic ranking scheme is being used, the use of phrases does not have a major e ect on precision at high ranks. Phrases are more useful at lower ranks where the connection between documents and relevance is more tenuous. Also, we nd that the syntactic and statistical methods for recognizing phrases yield comparable performance.

• Type: Conference
• Year: 1997
• Where: RIAO
• Authors: Mandar Mitra, Chris Buckley, Amit Singhal, Claire Cardie
• Keywords: Available Textual Data, RIAO 1997, RIAO 2007, Useful, World Wide Web