{"product_id":"natural-language-processing-and-text-mining-in-depth","title":"Natural Language Processing and Text Mining - In-depth","description":"\u003cp\u003eIn this review of Natural Language Processing and Text Mining the editors present a focused, conference-origin book that bridges two fields often treated separately. Intended for researchers and practitioners interested in the intersection of \u003cstrong\u003etext mining\u003c\/strong\u003e and \u003cstrong\u003enatural language processing\u003c\/strong\u003e, the book compiles discussions and papers that grew out of a 2004 ACM SIGKDD panel and a guest-edited special issue. The bottom line: this volume is most valuable as a snapshot of early cross-disciplinary thinking and practical perspectives rather than a modern textbook on algorithms.\u003c\/p\u003e\n\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eConference origins:\u003c\/strong\u003e Draws directly on a 2004 ACM SIGKDD panel that promoted dialogue between the two communities, providing historical context and real discussion points.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eEdited compilation:\u003c\/strong\u003e Curates insights from multiple contributors and a guest-edited special issue, offering a range of viewpoints rather than a single-author narrative.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePractical focus:\u003c\/strong\u003e Emphasizes how text mining and natural language processing can interact and benefit from each other in applied settings.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eScholarly audience:\u003c\/strong\u003e Serves as a resource for researchers who want to trace the development of interdisciplinary approaches and study panel-driven debate.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePublished by a major academic publisher:\u003c\/strong\u003e Indicates editorial standards and availability to academic readers interested in KDD community outcomes.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eWho It's For\u003c\/h2\u003e\n\u003cp\u003eThe book is best for graduate students, researchers, and data scientists who want historical and applied perspectives on how \u003cstrong\u003eNLP\u003c\/strong\u003e and \u003cstrong\u003etext mining\u003c\/strong\u003e communities began to collaborate during the early 2000s. It is also useful for conference attendees and academics tracing the evolution of knowledge discovery discussions.\u003c\/p\u003e\n\n\u003cp\u003eIt is less suitable for readers seeking a modern, hands-on textbook with contemporary tools, code examples, or the latest deep learning methods; those readers should look for more recent practical guides or tutorials focused on current frameworks.\u003c\/p\u003e\n\n\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003ePros\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eProvides authentic, conference-derived discussion that highlights cross-disciplinary challenges and opportunities.\u003c\/li\u003e\n\u003cli\u003eCollects diverse authored perspectives in one place, useful for literature reviews and historical context.\u003c\/li\u003e\n\u003cli\u003ePublished and edited with academic standards, making it reliable for citation and scholarly reference.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003eCons\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eNot a contemporary practical manual; it does not replace modern algorithmic textbooks or hands-on guides.\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eTitle\u003c\/td\u003e\n\u003ctd\u003eNatural Language Processing and Text Mining\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eEditors\u003c\/td\u003e\n\u003ctd\u003eAnne Kao, Steve R. Poteet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOrigin\u003c\/td\u003e\n\u003ctd\u003eBased on a 2004 ACM SIGKDD panel and guest-edited special issue\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eScope\u003c\/td\u003e\n\u003ctd\u003eInterdisciplinary discussion of text mining and natural language processing\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eAudience\u003c\/td\u003e\n\u003ctd\u003eResearchers, graduate students, and practitioners in KDD and NLP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher intent\u003c\/td\u003e\n\u003ctd\u003eAcademic publication aiming to document community discussion and papers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eOur Verdict\u003c\/h2\u003e\n\u003cp\u003eThis edited volume is a concise, useful record of early efforts to integrate \u003cstrong\u003etext mining\u003c\/strong\u003e and \u003cstrong\u003enatural language processing\u003c\/strong\u003e. It is good value for readers seeking historical context, scholarly perspectives, and a compilation of panel-derived papers, but not for those needing up-to-date tutorials or coding examples.\u003c\/p\u003e\n\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cp\u003e\u003cstrong\u003eIs this book based on real conference material?\u003c\/strong\u003e\u003cbr\u003eYes. The content originates from a 2004 ACM SIGKDD panel and a guest-edited special issue assembled by the editors.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eWho edited the collection?\u003c\/strong\u003e\u003cbr\u003eThe volume was edited by Anne Kao and Steve R. Poteet, who organized the original panel and related special issue.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eIs this suitable for hands-on learning?\u003c\/strong\u003e\u003cbr\u003eNot primarily; it is more valuable for historical and scholarly insight than for practical tutorials or current code examples.\u003c\/p\u003e","brand":"Anne Kao, Steve R. Poteet","offers":[{"title":"Default Title","offer_id":48258599649499,"sku":"1849965587","price":134.31,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0724\/1043\/1707\/files\/61uGpIctLnL._SL1263.jpg?v=1778278716","url":"https:\/\/gearmusthave.com\/products\/natural-language-processing-and-text-mining-in-depth","provider":"GearMustHave","version":"1.0","type":"link"}