๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Learning to Rank for Information Retrieval and Natural Language Processing

โœ Scribed by Hang Li


Publisher
Morgan & Claypool Publishers
Year
2011
Tongue
English
Leaves
115
Series
Synthesis Lectures on Human Language Technologies
Edition
1
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Subjects


ะ˜ะฝั„ะพั€ะผะฐั‚ะธะบะฐ ะธ ะฒั‹ั‡ะธัะปะธั‚ะตะปัŒะฝะฐั ั‚ะตั…ะฝะธะบะฐ;ะ˜ัะบัƒััั‚ะฒะตะฝะฝั‹ะน ะธะฝั‚ะตะปะปะตะบั‚;ะ˜ะฝั‚ะตะปะปะตะบั‚ัƒะฐะปัŒะฝั‹ะน ะฐะฝะฐะปะธะท ะดะฐะฝะฝั‹ั…;


๐Ÿ“œ SIMILAR VOLUMES


Learning to Rank for Information Retriev
โœ Hang Li ๐Ÿ“‚ Library ๐Ÿ“… 2015 ๐Ÿ› Morgan & Claypool ๐ŸŒ English

Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant prog

Learning to Rank for Information Retriev
โœ Tie-Yan Liu (auth.) ๐Ÿ“‚ Library ๐Ÿ“… 2011 ๐Ÿ› Springer-Verlag Berlin Heidelberg ๐ŸŒ English

<p><p>Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people.</p><p>The ranker, a central component in every

Learning to Rank for Information Retriev
โœ Tie-Yan Liu ๐Ÿ“‚ Library ๐Ÿ“… 2011 ๐Ÿ› Springer Science & Business Media ๐ŸŒ English

Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engin

Graph-based Natural Language Processing
โœ Rada F. Mihalcea, Dragomir R. Radev ๐Ÿ“‚ Library ๐Ÿ“… 2011 ๐Ÿ› Cambridge University Press ๐ŸŒ English

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications, and different potential end-users. However, recent research has shown that