As online information grows dramatically, search engines such as Google are playing a more and more important role in our lives. Critical to all search engines is the problem of designing an effective retrieval model that can rank documents accurately for a given query. This has been a central research problem in information retrieval for several decades. In the past ten years, a new generation of retrieval models, often referred to as statistical language models, has been successfully applied to solve many different information retrieval problems. Compared with the traditional models such as the vector space model, these new models have a more sound statistical foundation and can leverage statistical estimation to optimize retrieval parameters. They can also be more easily adapted to model non-traditional and complex retrieval problems. Empirically, they tend to achieve comparable or better performance than a traditional model with less effort on parameter tuning. This book systematically reviews the large body of literature on applying statistical language models to information retrieval with an emphasis on the underlying principles, empirically effective language models, and language models developed for non-traditional retrieval tasks. All the relevant literature has been synthesized to make it easy for a reader to digest the research progress achieved so far and see the frontier of research in this area. The book also offers practitioners an informative introduction to a set of practically useful language models that can effectively solve a variety of retrieval problems. No prior knowledge about information retrieval is required, but some basic knowledge about probability and statistics would be useful for fully digesting all the details.
發表於2024-12-23
Statistical Language Models for Information Retrieval 2024 pdf epub mobi 電子書 下載
Language Model是Information Retrieval領域最近10年左右發展起來的一個新的模型,相比於舊的Vector Space Model和傳統的概率模型,Language Model有更好的理論基礎。 此書是在Language Model領域活躍的華裔科學傢ChengXiang Zhai所寫,非常淺顯易懂。其中不乏一些在論文中沒...
評分Language Model是Information Retrieval領域最近10年左右發展起來的一個新的模型,相比於舊的Vector Space Model和傳統的概率模型,Language Model有更好的理論基礎。 此書是在Language Model領域活躍的華裔科學傢ChengXiang Zhai所寫,非常淺顯易懂。其中不乏一些在論文中沒...
評分Language Model是Information Retrieval領域最近10年左右發展起來的一個新的模型,相比於舊的Vector Space Model和傳統的概率模型,Language Model有更好的理論基礎。 此書是在Language Model領域活躍的華裔科學傢ChengXiang Zhai所寫,非常淺顯易懂。其中不乏一些在論文中沒...
評分Language Model是Information Retrieval領域最近10年左右發展起來的一個新的模型,相比於舊的Vector Space Model和傳統的概率模型,Language Model有更好的理論基礎。 此書是在Language Model領域活躍的華裔科學傢ChengXiang Zhai所寫,非常淺顯易懂。其中不乏一些在論文中沒...
評分Language Model是Information Retrieval領域最近10年左右發展起來的一個新的模型,相比於舊的Vector Space Model和傳統的概率模型,Language Model有更好的理論基礎。 此書是在Language Model領域活躍的華裔科學傢ChengXiang Zhai所寫,非常淺顯易懂。其中不乏一些在論文中沒...
圖書標籤: 信息檢索 ir 機器學習 NLP 統計語言模型 人工智能 搜索引擎 人工智能與信息處理
Statistical Language Models for Information Retrieval 2024 pdf epub mobi 電子書 下載