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|a International Symposium on Intelligent Systems Technologies and Applications
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|a Intelligent systems, technologies and applications
|b proceedings of ISTA 2018
|c Sabu M. Thampi, [and 7 others], editors
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|a 1 online resource (289 pages).
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|a Advances in intelligent systems and computing ;
|v volume 910
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0 |
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|a Intro; Organization; Chief Patron; Patrons; General Chairs; General Executive Chair; Steering Committee Chairs; Organizing Chair; Organizing Co-chairs; Technical Program Chairs; Organizing Secretaries; TPC Members/Additional Reviewers; Preface; Contents; About the Editors; Dynamic Mode-Based Feature with Random Mapping for Sentiment Analysis; 1 Introduction; 2 Background; 2.1 Dynamic Mode Decomposition (DMD); 2.2 Random Mapping Approach Using Random Kitchen Sink (RKS); 2.3 Regularized Least Square-Based Classification (RLSC); 3 Proposed Approach; 3.1 Step 1: Preprocessing
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| 505 |
8 |
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|a 3.2 Step 2: Tweet Vector3.3 Step 3: DMD-Based Dynamic Mode Feature Extraction; 3.4 Step 4: Random Mapping with RKS; 3.5 Step 5: Regularized Least Square-Based Classification; 4 Dataset Description; 5 Results; 5.1 Result of Evaluation for SAIL 2015 Shared Task Dataset; 5.2 Result of Evaluation for Malayalam Dataset; 5.3 Discussion; 6 Conclusion; References; Efficient Pre-processing and Feature Selection for Clustering of Cancer Tweets; 1 Introduction; 2 Related Work; 3 Proposed Methodology; 3.1 Data Collection and Pre-processing; 3.2 Clustering; 3.3 Feature Selection; 3.4 Feature Extraction
|
| 505 |
8 |
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|a 3.5 Summary Evaluation4 Experiments and Results; 5 Conclusion; References; Intrinsic Evaluation for English-Tamil Bilingual Word Embeddings; 1 Introduction; 2 Evaluating Word Embeddings; 3 Experimental Design; 3.1 Semantic Similarity and Relatedness; 3.2 Lexical Gaps in English-Tamil Bilingual domain; 3.3 Morphological Gaps; 4 Dataset Description; 5 Scoring Scheme; 5.1 Evaluator Instructions; 5.2 Statistical Pruning of Human Evaluation Scores; 6 Result; 7 Conclusion; References; A Novel Approach of Augmenting Training Data for Legal Text Segmentation by Leveraging Domain Knowledge
|
| 505 |
8 |
|
|a 1 Introduction2 Literature Review; 3 Proposed Approach; 3.1 Position Based Segmentation; 3.2 Keyword Based Segmentation; 4 Experimental Evaluation; 4.1 Experimental Setup; 4.2 Experimental Results; 5 Conclusion; References; Sarcasm Detection on Twitter: User Behavior Approach; 1 Introduction; 2 Literature Survey; 2.1 Sentiment-Related Features; 2.2 Punctuation-Related Features; 2.3 Syntactic and Semantic Features; 2.4 Pattern-Related Features; 3 Issues; 4 User Behavior Approach; 4.1 Part A: User Behavior Pattern; 4.2 Part B: Context Evaluation; 5 Conclusion; References
|
| 505 |
8 |
|
|a Personalized Recommender Agent for E-Commerce Products Based on Data Mining Techniques1 Introduction; 2 Related Work; 3 Recommendation Approach and Model; 3.1 Phase I: Pre-processing Unit; 3.2 Phase II: Clustering and Neighborhood Formation; 3.3 Phase III: Finding Association Among Products; 4 Experiments and Results; 4.1 Steps for Recommender Evaluation; 4.2 Evaluation Measures; 4.3 Evaluation of Proposed and Conventional RSs; 5 Conclusion and Future Work; References; Pep-Personalized Educational Platform; 1 Introduction; 2 Methodology; 2.1 Modules; 2.2 Features; 2.3 Scheduling Algorithm
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International Symposium on Intelligent Systems Technologies and Applications (4th : 2018 : Bangalore, India) |
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Intro; Organization; Chief Patron; Patrons; General Chairs; General Executive Chair; Steering Committee Chairs; Organizing Chair; Organizing Co-chairs; Technical Program Chairs; Organizing Secretaries; TPC Members/Additional Reviewers; Preface; Contents; About the Editors; Dynamic Mode-Based Feature with Random Mapping for Sentiment Analysis; 1 Introduction; 2 Background; 2.1 Dynamic Mode Decomposition (DMD); 2.2 Random Mapping Approach Using Random Kitchen Sink (RKS); 2.3 Regularized Least Square-Based Classification (RLSC); 3 Proposed Approach; 3.1 Step 1: Preprocessing, 3.2 Step 2: Tweet Vector3.3 Step 3: DMD-Based Dynamic Mode Feature Extraction; 3.4 Step 4: Random Mapping with RKS; 3.5 Step 5: Regularized Least Square-Based Classification; 4 Dataset Description; 5 Results; 5.1 Result of Evaluation for SAIL 2015 Shared Task Dataset; 5.2 Result of Evaluation for Malayalam Dataset; 5.3 Discussion; 6 Conclusion; References; Efficient Pre-processing and Feature Selection for Clustering of Cancer Tweets; 1 Introduction; 2 Related Work; 3 Proposed Methodology; 3.1 Data Collection and Pre-processing; 3.2 Clustering; 3.3 Feature Selection; 3.4 Feature Extraction, 3.5 Summary Evaluation4 Experiments and Results; 5 Conclusion; References; Intrinsic Evaluation for English-Tamil Bilingual Word Embeddings; 1 Introduction; 2 Evaluating Word Embeddings; 3 Experimental Design; 3.1 Semantic Similarity and Relatedness; 3.2 Lexical Gaps in English-Tamil Bilingual domain; 3.3 Morphological Gaps; 4 Dataset Description; 5 Scoring Scheme; 5.1 Evaluator Instructions; 5.2 Statistical Pruning of Human Evaluation Scores; 6 Result; 7 Conclusion; References; A Novel Approach of Augmenting Training Data for Legal Text Segmentation by Leveraging Domain Knowledge, 1 Introduction2 Literature Review; 3 Proposed Approach; 3.1 Position Based Segmentation; 3.2 Keyword Based Segmentation; 4 Experimental Evaluation; 4.1 Experimental Setup; 4.2 Experimental Results; 5 Conclusion; References; Sarcasm Detection on Twitter: User Behavior Approach; 1 Introduction; 2 Literature Survey; 2.1 Sentiment-Related Features; 2.2 Punctuation-Related Features; 2.3 Syntactic and Semantic Features; 2.4 Pattern-Related Features; 3 Issues; 4 User Behavior Approach; 4.1 Part A: User Behavior Pattern; 4.2 Part B: Context Evaluation; 5 Conclusion; References, Personalized Recommender Agent for E-Commerce Products Based on Data Mining Techniques1 Introduction; 2 Related Work; 3 Recommendation Approach and Model; 3.1 Phase I: Pre-processing Unit; 3.2 Phase II: Clustering and Neighborhood Formation; 3.3 Phase III: Finding Association Among Products; 4 Experiments and Results; 4.1 Steps for Recommender Evaluation; 4.2 Evaluation Measures; 4.3 Evaluation of Proposed and Conventional RSs; 5 Conclusion and Future Work; References; Pep-Personalized Educational Platform; 1 Introduction; 2 Methodology; 2.1 Modules; 2.2 Features; 2.3 Scheduling Algorithm |
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International Symposium on Intelligent Systems Technologies and Applications (4th : 2018 : Bangalore, India), Intelligent systems, technologies and applications proceedings of ISTA 2018 Sabu M. Thampi, [and 7 others], editors, ISTA 2018, Singapore Springer 2020, ©2020, 1 online resource (289 pages)., text rdacontent, computer rdamedia, online resource rdacarrier, Advances in intelligent systems and computing ; volume 910, Intro; Organization; Chief Patron; Patrons; General Chairs; General Executive Chair; Steering Committee Chairs; Organizing Chair; Organizing Co-chairs; Technical Program Chairs; Organizing Secretaries; TPC Members/Additional Reviewers; Preface; Contents; About the Editors; Dynamic Mode-Based Feature with Random Mapping for Sentiment Analysis; 1 Introduction; 2 Background; 2.1 Dynamic Mode Decomposition (DMD); 2.2 Random Mapping Approach Using Random Kitchen Sink (RKS); 2.3 Regularized Least Square-Based Classification (RLSC); 3 Proposed Approach; 3.1 Step 1: Preprocessing, 3.2 Step 2: Tweet Vector3.3 Step 3: DMD-Based Dynamic Mode Feature Extraction; 3.4 Step 4: Random Mapping with RKS; 3.5 Step 5: Regularized Least Square-Based Classification; 4 Dataset Description; 5 Results; 5.1 Result of Evaluation for SAIL 2015 Shared Task Dataset; 5.2 Result of Evaluation for Malayalam Dataset; 5.3 Discussion; 6 Conclusion; References; Efficient Pre-processing and Feature Selection for Clustering of Cancer Tweets; 1 Introduction; 2 Related Work; 3 Proposed Methodology; 3.1 Data Collection and Pre-processing; 3.2 Clustering; 3.3 Feature Selection; 3.4 Feature Extraction, 3.5 Summary Evaluation4 Experiments and Results; 5 Conclusion; References; Intrinsic Evaluation for English-Tamil Bilingual Word Embeddings; 1 Introduction; 2 Evaluating Word Embeddings; 3 Experimental Design; 3.1 Semantic Similarity and Relatedness; 3.2 Lexical Gaps in English-Tamil Bilingual domain; 3.3 Morphological Gaps; 4 Dataset Description; 5 Scoring Scheme; 5.1 Evaluator Instructions; 5.2 Statistical Pruning of Human Evaluation Scores; 6 Result; 7 Conclusion; References; A Novel Approach of Augmenting Training Data for Legal Text Segmentation by Leveraging Domain Knowledge, 1 Introduction2 Literature Review; 3 Proposed Approach; 3.1 Position Based Segmentation; 3.2 Keyword Based Segmentation; 4 Experimental Evaluation; 4.1 Experimental Setup; 4.2 Experimental Results; 5 Conclusion; References; Sarcasm Detection on Twitter: User Behavior Approach; 1 Introduction; 2 Literature Survey; 2.1 Sentiment-Related Features; 2.2 Punctuation-Related Features; 2.3 Syntactic and Semantic Features; 2.4 Pattern-Related Features; 3 Issues; 4 User Behavior Approach; 4.1 Part A: User Behavior Pattern; 4.2 Part B: Context Evaluation; 5 Conclusion; References, Personalized Recommender Agent for E-Commerce Products Based on Data Mining Techniques1 Introduction; 2 Related Work; 3 Recommendation Approach and Model; 3.1 Phase I: Pre-processing Unit; 3.2 Phase II: Clustering and Neighborhood Formation; 3.3 Phase III: Finding Association Among Products; 4 Experiments and Results; 4.1 Steps for Recommender Evaluation; 4.2 Evaluation Measures; 4.3 Evaluation of Proposed and Conventional RSs; 5 Conclusion and Future Work; References; Pep-Personalized Educational Platform; 1 Introduction; 2 Methodology; 2.1 Modules; 2.2 Features; 2.3 Scheduling Algorithm, Artificial intelligence Congresses., Electronic books., Thampi, Sabu M. editor., Advances in intelligent systems and computing ; 910., ELD ebook, LDL ebooks ONIX to marcxml transformation using Record_Load-eBooks_Legal_Deposit_onix2marc_v2-1.xsl 20200612 com.springer.onix.9789811539145 Uk |
| spellingShingle |
Intelligent systems, technologies and applications: proceedings of ISTA 2018, Advances in intelligent systems and computing, 910, Intro; Organization; Chief Patron; Patrons; General Chairs; General Executive Chair; Steering Committee Chairs; Organizing Chair; Organizing Co-chairs; Technical Program Chairs; Organizing Secretaries; TPC Members/Additional Reviewers; Preface; Contents; About the Editors; Dynamic Mode-Based Feature with Random Mapping for Sentiment Analysis; 1 Introduction; 2 Background; 2.1 Dynamic Mode Decomposition (DMD); 2.2 Random Mapping Approach Using Random Kitchen Sink (RKS); 2.3 Regularized Least Square-Based Classification (RLSC); 3 Proposed Approach; 3.1 Step 1: Preprocessing, 3.2 Step 2: Tweet Vector3.3 Step 3: DMD-Based Dynamic Mode Feature Extraction; 3.4 Step 4: Random Mapping with RKS; 3.5 Step 5: Regularized Least Square-Based Classification; 4 Dataset Description; 5 Results; 5.1 Result of Evaluation for SAIL 2015 Shared Task Dataset; 5.2 Result of Evaluation for Malayalam Dataset; 5.3 Discussion; 6 Conclusion; References; Efficient Pre-processing and Feature Selection for Clustering of Cancer Tweets; 1 Introduction; 2 Related Work; 3 Proposed Methodology; 3.1 Data Collection and Pre-processing; 3.2 Clustering; 3.3 Feature Selection; 3.4 Feature Extraction, 3.5 Summary Evaluation4 Experiments and Results; 5 Conclusion; References; Intrinsic Evaluation for English-Tamil Bilingual Word Embeddings; 1 Introduction; 2 Evaluating Word Embeddings; 3 Experimental Design; 3.1 Semantic Similarity and Relatedness; 3.2 Lexical Gaps in English-Tamil Bilingual domain; 3.3 Morphological Gaps; 4 Dataset Description; 5 Scoring Scheme; 5.1 Evaluator Instructions; 5.2 Statistical Pruning of Human Evaluation Scores; 6 Result; 7 Conclusion; References; A Novel Approach of Augmenting Training Data for Legal Text Segmentation by Leveraging Domain Knowledge, 1 Introduction2 Literature Review; 3 Proposed Approach; 3.1 Position Based Segmentation; 3.2 Keyword Based Segmentation; 4 Experimental Evaluation; 4.1 Experimental Setup; 4.2 Experimental Results; 5 Conclusion; References; Sarcasm Detection on Twitter: User Behavior Approach; 1 Introduction; 2 Literature Survey; 2.1 Sentiment-Related Features; 2.2 Punctuation-Related Features; 2.3 Syntactic and Semantic Features; 2.4 Pattern-Related Features; 3 Issues; 4 User Behavior Approach; 4.1 Part A: User Behavior Pattern; 4.2 Part B: Context Evaluation; 5 Conclusion; References, Personalized Recommender Agent for E-Commerce Products Based on Data Mining Techniques1 Introduction; 2 Related Work; 3 Recommendation Approach and Model; 3.1 Phase I: Pre-processing Unit; 3.2 Phase II: Clustering and Neighborhood Formation; 3.3 Phase III: Finding Association Among Products; 4 Experiments and Results; 4.1 Steps for Recommender Evaluation; 4.2 Evaluation Measures; 4.3 Evaluation of Proposed and Conventional RSs; 5 Conclusion and Future Work; References; Pep-Personalized Educational Platform; 1 Introduction; 2 Methodology; 2.1 Modules; 2.2 Features; 2.3 Scheduling Algorithm, Artificial intelligence Congresses., Electronic books. |
| title |
Intelligent systems, technologies and applications: proceedings of ISTA 2018 |
| title_alt |
ISTA 2018 |
| title_auth |
Intelligent systems, technologies and applications proceedings of ISTA 2018 |
| title_full |
Intelligent systems, technologies and applications proceedings of ISTA 2018 Sabu M. Thampi, [and 7 others], editors |
| title_fullStr |
Intelligent systems, technologies and applications proceedings of ISTA 2018 Sabu M. Thampi, [and 7 others], editors |
| title_full_unstemmed |
Intelligent systems, technologies and applications proceedings of ISTA 2018 Sabu M. Thampi, [and 7 others], editors |
| title_in_hierarchy |
910.. Intelligent systems, technologies and applications: proceedings of ISTA 2018 (2020) |
| title_short |
Intelligent systems, technologies and applications |
| title_sort |
intelligent systems technologies and applications proceedings of ista 2018 |
| title_sub |
proceedings of ISTA 2018 |
| topic |
Artificial intelligence Congresses., Electronic books. |
| topic_facet |
Artificial intelligence, Electronic books. |