Mining search-phrase definitions from item descriptions

In this paper, we develop a model for representing term dependence based on Markov Random Fields and present an approach based on Markov Chain Monte Carlo technique for generating phrase definitions. This approach can use a small corpus of keyword matching and a random sample of other product descriptions for an advertiser's search-phrase to effectively mine and rank alternative but highly relevant search-phrase definitions. These definitions, which are search-phrases themselves, can then be provided as alternative phrases to an advertiser.