图书简介
Text analytics (TA) covers a very wide research area. Its overarching goal is to discover and present knowledge — facts, rules, and relationships — that is otherwise hidden in the textual content. The authors of this book guide us in a quest to attain this knowledge automatically, by applying various machine learning techniques.
This book describes recent development in multilingual text analysis. It covers several specific examples of practical TA applications, including their problem statements, theoretical background, and implementation of the proposed solution. The reader can see which preprocessing techniques and text representation models were used, how the evaluation process was designed and implemented, and how these approaches can be adapted to multilingual domains.
MultiLingual Text Analysis; Using a Polytope Model for Summarization; MDL Model for Summarization; Feature Spaces and Regression Models for Summarization; Hierarchical Topic Model and Summarization; A Survey of Neural Models in Abstractive Summarization; HEADS: Headline Generation as a Sequence Prediction; Crowdsourcing in Single-document Summary Evaluation; Multilingual Summarization and Evaluation; Analyzing Text Complexity in Automatic Summarization; Twitter Event Analysis; Linguistic Bias in Crowdsourced Biographies; Multilingual Financial Narrative Processing
Key Features:
○Summarizes up-to-date research of MultiLing scientific community
○Focuses on language-independent methods and models
○Broad range of text analysis tasks is covered
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