| LDR | | 04992cmm u2200577Ii 4500 |
| 001 | | 000000311040 |
| 003 | | OCoLC |
| 005 | | 20230525141430 |
| 006 | | m o d |
| 007 | | cr cnu|||unuuu |
| 008 | | 170711s2017 ne ob 000 0 eng d |
| 020 | |
▼a 9781614997511
▼q (electronic bk.) |
| 020 | |
▼a 1614997519
▼q (electronic bk.) |
| 020 | |
▼z 9781614997504
▼q (print) |
| 029 | 1 |
▼a CHVBK
▼b 495243884 |
| 029 | 1 |
▼a CHNEW
▼b 000966534 |
| 035 | |
▼a (OCoLC)993432979 |
| 040 | |
▼a N$T
▼b eng
▼e rda
▼e pn
▼c N$T
▼d IOSPR
▼d IDEBK
▼d EBLCP
▼d BTCTA
▼d N$T
▼d OCLCF
▼d OCLCQ
▼d MERUC
▼d IDB
▼d YDX
▼d 248032 |
| 049 | |
▼a MAIN |
| 050 | 4 |
▼a QA76.5913 |
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▼a COM
▼x 000000
▼2 bisacsh |
| 082 | 04 |
▼a 006
▼2 23 |
| 100 | 1 |
▼a Saif, Hassan,
▼e author. |
| 245 | 10 |
▼a Semantic sentiment analysis in social streams /
▼c Hassan Saif. |
| 264 | 1 |
▼a Amsterdam, Netherlands :
▼b IOS Press ;
▼a Berlin, Germany :
▼b Akademische Verlagsgesellschaft,
▼c 2017. |
| 300 | |
▼a 1 online resource. |
| 336 | |
▼a text
▼b txt
▼2 rdacontent |
| 337 | |
▼a computer
▼b c
▼2 rdamedia |
| 338 | |
▼a online resource
▼b cr
▼2 rdacarrier |
| 490 | 1 |
▼a Studies on the semantic web ;
▼v vol. 030 |
| 504 | |
▼a Includes bibliographical references. |
| 505 | 0 |
▼a Title Page; Dedication; Statement; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; 1 Introduction; 1.1 Motivation; 1.1.1 Sentiment Analysis of Twitter: Gaps and Challenges; 1.1.2 From Affect Words to Words' Semantics; 1.2 Research Questions, Hypotheses and Contributions; 1.3 Thesis Methodology and Outline; 1.4 Publications; Background; 2 Literature Review; 2.1 Background; 2.1.1 Fundamentals; 2.1.2 A Note on Terminology; 2.2 Sentiment Analysis of Twitter; 2.2.1 Traditional Sentiment Analysis Approaches; 2.2.1.1 The Machine Learning Approach |
| 505 | 8 |
▼a 2.2.1.2 The Lexicon-based Approach2.2.1.3 The Hybrid Approach; 2.2.1.4 Discussion; 2.3 Semantic Sentiment Analysis; 2.3.1 Contextual Semantics; 2.3.2 Conceptual Semantics; 2.4 Summary and Discussion; 2.4.1 Discussion; Semantic Sentiment Analysis of Twitter; 3 Contextual Semantics for Sentiment Analysis of Twitter; 3.1 Introduction; 3.2 The SentiCircle Representation of Words' Semantics; 3.2.1 Overview; 3.2.2 SentiCircle Construction Pipeline; 3.2.2.1 Term Indexing; 3.2.2.2 Context Vector Generation; 3.2.2.3 SentiCircle Generation; 3.2.2.4 Senti-Median: The Overall Contextual Sentiment Value |
| 505 | 8 |
▼a 3.3 SentiCircles for Sentiment Analysis3.3.1 Entity-level Sentiment Detection; 3.3.2 Tweet-level Sentiment Detection; 3.3.2.1 The Median Method; 3.3.2.2 The Pivot Method; 3.3.2.3 The Pivot-Hybrid Method; 3.3.3 Evaluation Setup; 3.3.3.1 Datasets; 3.3.3.2 Sentiment Lexicons; 3.3.3.3 Baselines; 3.3.3.4 Thresholds and Parameters Tuning; 3.3.4 Evaluation Results; 3.3.4.1 Entity-Level Sentiment Detection; 3.3.4.2 Tweet-Level Sentiment Detection; 3.3.4.3 Impact on Words' Sentiment; 3.4 SentiCircles for Adapting Sentiment Lexicons; 3.4.1 Evaluating SentiStrength on the Adapted Thelwall-Lexicon |
| 505 | 8 |
▼a 3.5 Runtime Analysis3.6 Discussion; 3.7 Summary; 4 Conceptual Semantics for Sentiment Analysis of Twitter; 4.1 Introduction; 4.2 Conceptual Semantics for Supervised Sentiment Analysis; 4.2.1 Extracting Conceptual Semantics; 4.2.2 Conceptual Semantics Incorporation; 4.2.3 Evaluation Setup; 4.2.3.1 Datasets; 4.2.3.2 Semantic Concepts Extraction; 4.2.3.3 Baselines; 4.2.4 Evaluation Results; 4.2.4.1 Results on Incorporating Semantic Features; 4.2.4.2 Comparison of Results; 4.3 Conceptual Semantics for Lexicon-based Sentiment Analysis; 4.3.1 Enriching SentiCircles with Conceptual Semantics |
| 505 | 8 |
▼a 4.3.2 Evaluation Results4.4 Discussion; 4.5 Summary; 5 Semantic Patterns for Sentiment Analysis of Twitter; 5.1 Introduction; 5.2 Related Work; 5.3 Semantic Sentiment Patterns of Words; 5.3.1 Syntactical Preprocessing; 5.3.2 Capturing Contextual Semantics and Sentiment of Words; 5.3.3 Extracting Patterns from SentiCircles; 5.4 Evaluation Setup; 5.4.1 Tweet-Level Evaluation Setup; 5.4.2 Entity-Level Evaluation Setup; 5.4.3 Evaluation Baselines; 5.4.4 Number of SS-Patterns in Data; 5.5 Evaluation Results; 5.5.1 Results of Tweet-Level Sentiment Classification |
| 588 | 0 |
▼a Online resource; title from PDF title page (IOS Press, viewed July 11, 2017). |
| 590 | |
▼a eBooks on EBSCOhost
▼b All EBSCO eBooks |
| 650 | 0 |
▼a Semantic computing. |
| 650 | 0 |
▼a Social media. |
| 650 | 7 |
▼a COMPUTERS / General
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▼a Social media.
▼2 fast
▼0 (OCoLC)fst01741098 |
| 655 | 4 |
▼a Electronic books. |
| 830 | 0 |
▼a Studies on the Semantic Web ;
▼v vol. 030. |
| 856 | 40 |
▼u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1549267 |
| 938 | |
▼a YBP Library Services
▼b YANK
▼n 14681531 |
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▼b EBLB
▼n EBL4908232 |
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▼a ProQuest MyiLibrary Digital eBook Collection
▼b IDEB
▼n cis38464111 |
| 938 | |
▼a EBSCOhost
▼b EBSC
▼n 1549267 |
| 938 | |
▼a Baker and Taylor
▼b BTCP
▼n BK0021159548 |
| 990 | |
▼a 관리자 |