Natural Language Processing and Text Mining
暫譯: 自然語言處理與文本挖掘
Anne Kao, Steve R. Poteet
- 出版商: Springer
- 出版日期: 2006-12-12
- 售價: $3,600
- 貴賓價: 9.5 折 $3,420
- 語言: 英文
- 頁數: 265
- 裝訂: Hardcover
- ISBN: 184628175X
- ISBN-13: 9781846281754
-
相關分類:
Text-mining
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商品描述
Description
With the increasing importance of the Web and other text-heavy application areas, the demands for and interest in both text mining and natural language processing (NLP) have been rising. Researchers in text mining have hoped that NLP—the attempt to extract a fuller meaning representation from free text—can provide useful improvements to text mining applications of all kinds.
Bringing together a variety of perspectives from internationally renowned researchers, Natural Language Processing and Text Mining not only discusses applications of certain NLP techniques to certain Text Mining tasks, but also the converse, i.e., use of Text Mining to facilitate NLP. It explores a variety of real-world applications of NLP and text-mining algorithms in comprehensive detail, placing emphasis on the description of end-to-end solutions to real problems, and detailing the associated difficulties that must be resolved before the algorithm can be applied and its full benefits realized. In addition, it explores a number of cutting-edge techniques and approaches, as well as novel ways of integrating various technologies. Nevertheless, even readers with only a basic knowledge of data mining or text mining will benefit from the many illustrative examples and solutions.
Topics and features:
• Describes novel and high-impact text mining and/or natural language applications
• Points out typical traps in trying to apply NLP to text mining
• Illustrates preparation and preprocessing of text data – offering practical issues and examples
• Surveys related supporting techniques, problem types, and potential technique enhancements
• Examines the interaction of text mining and NLP
This state-of-the-art, practical volume will be an essential resource for professionals and researchers who wish to learn how to apply text mining and language processing techniques to real world problems. In addition, it can be used as a supplementary text for advanced students studying text mining and NLP.
Table of Contents
Overview.- Extracting Product Features and Opinions from Reviews.- Extracting Relations from Text.- Mining Diagnostic Text Reports by Learning to Annotate Knowledge Roles.- A Case Study in Natural Language Based Web Search.- Evaluating Self-explanations in iSTART:Word Matching, Latent Semantic Analysis, and Topic Models.- Textual Signatures: Identifying Text-Types Using Latent Semantic Analysis to Measure the Cohesion of Text Structures.- Automatic Document Separation - A Combination of Probabilistic Classification and Finite-State Sequence Modeling.- Evolving Explanatory Novel Patterns for Semantically-based Text Mining.- Handling of Imbalanced Data in Text Classification: Category Based Term Weights.- Automatic Evaluation of Ontologies.- Linguistic Computing with UNIX Tools.- Index
商品描述(中文翻譯)
**描述**
隨著網路及其他以文字為主的應用領域的重要性日益增加,對於文本挖掘(text mining)和自然語言處理(Natural Language Processing, NLP)的需求和興趣也在上升。文本挖掘的研究者希望NLP——從自由文本中提取更完整的意義表示的嘗試——能為各種文本挖掘應用提供有用的改進。
《自然語言處理與文本挖掘》匯集了來自國際知名研究者的多種觀點,不僅討論了某些NLP技術在特定文本挖掘任務中的應用,還探討了相反的情況,即利用文本挖掘來促進NLP。它詳細探討了NLP和文本挖掘算法在現實世界中的多種應用,強調針對實際問題的端到端解決方案的描述,並詳細說明在應用算法之前必須解決的相關困難。此外,它還探討了一些前沿技術和方法,以及整合各種技術的新穎方式。儘管如此,即使是對數據挖掘或文本挖掘只有基本了解的讀者,也能從許多示例和解決方案中受益。
主題和特點:
- 描述新穎且高影響力的文本挖掘和/或自然語言應用
- 指出在嘗試將NLP應用於文本挖掘時的典型陷阱
- 說明文本數據的準備和預處理——提供實際問題和示例
- 調查相關的支持技術、問題類型和潛在的技術增強
- 檢視文本挖掘和NLP之間的互動
這本最先進的實用書籍將成為希望學習如何將文本挖掘和語言處理技術應用於現實問題的專業人士和研究者的重要資源。此外,它也可以作為進階學生學習文本挖掘和NLP的補充教材。
**目錄**
概述 - 從評論中提取產品特徵和意見 - 從文本中提取關係 - 通過學習註解知識角色來挖掘診斷文本報告 - 基於自然語言的網路搜索案例研究 - 評估iSTART中的自我解釋:詞匹配、潛在語義分析和主題模型 - 文本簽名:使用潛在語義分析識別文本類型以測量文本結構的凝聚力 - 自動文檔分離 - 機率分類和有限狀態序列建模的結合 - 為基於語義的文本挖掘演變解釋性新模式 - 在文本分類中處理不平衡數據:基於類別的術語權重 - 本體的自動評估 - 使用UNIX工具的語言計算 - 索引