Dissertation Information for Victor LavrenkoNAME:
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SCHOOL: ADVISORS: COMMITTEE MEMBERS: MPACT Status: Fully Complete Title: A generative theory of relevance Abstract: We present a new theory of relevance for the field of Information Retrieval. Relevance is viewed as a generative process, and we hypothesize that both user queries and relevant documents represent random observations from that process. Based on this view, we develop a formal retrieval model that has direct applications to a wide range of search scenarios. The new model substantially outperforms strong baselines on the tasks of ad-hoc retrieval, cross-language retrieval, handwriting retrieval, automatic image annotation, video retrieval, and topic detection and tracking. Empirical success of our approach is due to a new technique we propose for modeling exchangeable sequences of discrete random variables. The new technique represents an attractive counterpart to existing formulations, such as multinomial mixtures, pLSI and LDA: it is effective, easy to train, and makes no assumptions about the geometric structure of the data. |
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