Abstract not found

Statistical language models have recently been successfully applied to many information retrieval problems. A great deal of recent work has shown that statistical language models not only lead to superior empirical performance, but also facilitate parameter tuning and open up possibilities for modeling nontraditional retrieval problems. In general, statistical language models provide a principled way of modeling various kinds of retrieval problems. The purpose of this survey is to systematically and critically review the existing work in applying statistical language models to information retrieval, summarize their contributions, and point out outstanding challenges. 1

Mining textual documents and time series concurrently, such as predicting the movements of stock prices based on the contents of the news stories, is an emerging topic in data mining community. Previous researches have shown that there is a strong relationship between the time when the news stories are released and the time when the stock prices fluctuate. In this paper, we propose a systematic framework for predicting the tertiary movements of stock prices by analyzing the impacts of the news stories on the stocks. To be more specific, we investigate the immediate impacts of news stories on the stocks based on the Efficient Markets Hypothesis. Several data mining and text mining techniques are used in a novel way. Extensive experiments using real-life data are conducted, and encouraging results are obtained.

With the rapid growth of the Internet, how to get information from this huge information space becomes an even more important problem. In this paper, An Intelligence Chinese Document Semantic Indexing System; ICDSIS, is proposed. Some new technologies are integrated in ICDSIS to obtain good performance. ICDSIS is composed of four key procedures. A parallel, distributed and configurable Spider is used for information gather; a multi-hierarchy document classification approach combining the information gain initially processes gathered web documents; a swarm intelligence based document clustering method is used for information organization; a concept-based retrieval interface is applied for user interactive retrieval. ICDSIS is an all-sided solution for information retrieval on the Internet.