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001 978-3-031-01880-0
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008 220601s2011 sz | s |||| 0|eng d
020 _a9783031018800
_9978-3-031-01880-0
024 7 _a10.1007/978-3-031-01880-0
_2doi
050 4 _aTK5105.5-5105.9
072 7 _aUKN
_2bicssc
072 7 _aCOM043000
_2bisacsh
072 7 _aUKN
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082 0 4 _a004.6
_223
100 1 _aCarenini​‌, Giuseppe.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980352
245 1 0 _aMethods for Mining and Summarizing Text Conversations
_h[electronic resource] /
_cby Giuseppe Carenini​‌, Raymond Ng, Gabriel Murray.
250 _a1st ed. 2011.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2011.
300 _aX, 120 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Data Management,
_x2153-5426
505 0 _aIntroduction -- Background: Corpora and Evaluation Methods -- Mining Text Conversations -- Summarizing Text Conversations -- Conclusions -- Final Thoughts.
520 _aDue to the Internet Revolution, human conversational data -- in written forms -- are accumulating at a phenomenal rate. At the same time, improvements in speech technology enable many spoken conversations to be transcribed. Individuals and organizations engage in email exchanges, face-to-face meetings, blogging, texting and other social media activities. The advances in natural language processing provide ample opportunities for these "informal documents" to be analyzed and mined, thus creating numerous new and valuable applications. This book presents a set of computational methods to extract information from conversational data, and to provide natural language summaries of the data. The book begins with an overview of basic concepts, such as the differences between extractive and abstractive summaries, and metrics for evaluating the effectiveness of summarization and various extraction tasks. It also describes some of the benchmark corpora used in the literature. The book introducesextraction and mining methods for performing subjectivity and sentiment detection, topic segmentation and modeling, and the extraction of conversational structure. It also describes frameworks for conducting dialogue act recognition, decision and action item detection, and extraction of thread structure. There is a specific focus on performing all these tasks on conversational data, such as meeting transcripts (which exemplify synchronous conversations) and emails (which exemplify asynchronous conversations). Very recent approaches to deal with blogs, discussion forums and microblogs (e.g., Twitter) are also discussed. The second half of this book focuses on natural language summarization of conversational data. It gives an overview of several extractive and abstractive summarizers developed for emails, meetings, blogs and forums. It also describes attempts for building multi-modal summarizers. Last but not least, the book concludes with thoughts on topics for further development. Table of Contents: Introduction / Background: Corpora and Evaluation Methods / Mining Text Conversations / Summarizing Text Conversations / Conclusions / Final Thoughts.
650 0 _aComputer networks .
_931572
650 0 _aData structures (Computer science).
_98188
650 0 _aInformation theory.
_914256
650 1 4 _aComputer Communication Networks.
_980353
650 2 4 _aData Structures and Information Theory.
_931923
700 1 _aNg, Raymond.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980354
700 1 _aMurray, Gabriel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980355
710 2 _aSpringerLink (Online service)
_980356
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031007521
776 0 8 _iPrinted edition:
_z9783031030086
830 0 _aSynthesis Lectures on Data Management,
_x2153-5426
_980357
856 4 0 _uhttps://doi.org/10.1007/978-3-031-01880-0
912 _aZDB-2-SXSC
942 _cEBK
999 _c84944
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