LEADER 09875nam 22008055 450 001 9910255453203321 005 20200704133254.0 010 $a981-10-7359-7 024 7 $a10.1007/978-981-10-7359-5 035 $a(CKB)4100000001795008 035 $a(DE-He213)978-981-10-7359-5 035 $a(MiAaPQ)EBC5576481 035 $a(MiAaPQ)EBC6306863 035 $a(Au-PeEL)EBL5576481 035 $a(OCoLC)1066180460 035 $a(Au-PeEL)EBL6306863 035 $a(PPN)223956066 035 $a(EXLCZ)994100000001795008 100 $a20180119d2017 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aKnowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence $eSecond China Conference, CCKS 2017, Chengdu, China, August 26?29, 2017, Revised Selected Papers /$fedited by Juanzi Li, Ming Zhou, Guilin Qi, Ni Lao, Tong Ruan, Jianfeng Du 205 $a1st ed. 2017. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2017. 215 $a1 online resource (XIV, 173 p. 42 illus.) 225 1 $aCommunications in Computer and Information Science,$x1865-0929 ;$v784 311 $a981-10-7358-9 327 $aIntro -- Preface -- Organization -- Contents -- Knowledge Base Completion by Learning to Rank Model -- 1 Introduction -- 2 Learning to Rank Model -- 3 Experiments -- 4 Related Work -- 5 Conclusion -- References -- Path-Based Learning for Plant Domain Knowledge Graph -- Abstract -- 1 Introduction -- 2 Approach -- 2.1 TransE Model -- 2.2 PTA Model -- 2.3 PTA (Path-Based TransE for Attributes) -- 2.4 Model Formulation -- 3 Experiments -- 3.1 Setup -- 3.2 Evaluation -- 4 Conclusion -- References -- A Graph-Based Approach to Incremental Classification in OWL 2 QL Ontology -- 1 Introduction -- 2 Preliminaries -- 2.1 OWL 2 QL -- 2.2 Graph Theory Notions -- 2.3 Digraph Representation of OWL QL 2 Ontologies -- 3 Mapping Ontologies Direct Graphs -- 4 Identifying Affected Paths and Updating Transitive Closure -- 5 Optimization -- 6 Implementation and Evaluation -- 7 Discussions -- References -- Tensor-Based Representation and Reasoning of Horn-SHOIQ Ontologies -- 1 Introduction -- 2 Ontology and Tensor Operations -- 3 A Tensor-Based Representation for Ontologies -- 4 Materialization via Tensor Operations -- 5 Conclusions and Future Work -- References -- Attention-Based Event Relevance Model for Stock Price Movement Prediction -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Problem Formulation -- 3.2 Attention-Based Event Relevance Model -- 3.3 Model Training -- 4 Experiments and Results -- 4.1 Dataset Construction -- 4.2 Implementation and Hyper-Parameter Setting -- 4.3 Stock Price Movement Prediction Experiments -- 4.4 Short-Term, Medium-Term, Long-Term Influence -- 5 Conclusion and Future Work -- References -- A Survey on Relation Extraction -- Abstract -- 1 Introduction -- 2 Datasets for Relation Extraction -- 3 Mainstream Methods -- 3.1 Rule-Based Approaches -- 3.2 Statistic-Based Approaches -- 4 Open Information Extraction (OIE). 327 $a5 Challenges and Directions -- 6 Conclusion -- Acknowledgment -- References -- A Sentiment and Topic Model with Timeslice, User and Hashtag for Posts on Social Media -- 1 Introduction -- 2 Sentiment Topic Model for Posts -- 3 Experiment -- 3.1 Dataset Description and Parameter Settings -- 3.2 Topic Coherence -- 3.3 Topic Visualization -- 4 Conclusion and Future Work -- References -- Collective Entity Linking Based on DBpedia -- Abstract -- 1 Introduction -- 2 Relate Work -- 3 Preliminary -- 4 Method Description -- 4.1 Candidate Entity Generation -- 4.2 Candidate Entity Selection -- 5 Evaluation -- 5.1 Dataset Description -- 5.2 Evaluation Criteria -- 5.3 Experimental Results -- 6 Conclusion and Future Work -- Acknowledgements -- References -- A CWTM Model of Topic Extraction for Short Text -- Abstract -- 1 Introduction -- 2 Related Work -- 3 A Novel Topic Modeling -- 3.1 Couple Word -- 3.2 Our Approach -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Micro-blog User Community Detection by Focusing on Micro-blog Content and Community Structure -- 1 Introduction -- 2 Related Work -- 3 Establish the Micro-blog Network -- 4 Detect the Objects' Clustering Directions -- 5 Detect Community -- 6 Experiments -- 6.1 Evaluate by the Interest Cohesion -- 6.2 Evaluate by the Community Structure -- 7 Conclusion and Future Work -- References -- Embedding Syntactic Tree Structures into CNN Architecture for Relation Classification -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Our Method -- 3.1 Feature Extraction -- 3.1.1 Syntactic Parsing Tree Embedding Features -- 3.1.2 Lexical Level Features -- 3.1.3 Entities Parsing Tree Embedding Features -- 3.2 Convolution Operation -- 3.3 Max-pooling Operation -- 3.4 Linear Transformation -- 3.5 Output -- 3.6 Dropout Operation -- 3.7 Training Procedure -- 4 Experiments -- 5 Conclusions. 327 $aAcknowledgements -- References -- Tracking Topic Trends for Short Texts -- 1 Introduction -- 2 Related Work -- 3 Topic Trend Detection (TTD) Model -- 3.1 Pre-process Stage -- 3.2 An Optimized Topic Model -- 3.3 Auxiliary Word Embeddings -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Evaluation by Topic Coherence -- 4.4 Trend Detection in Microblog -- 5 Conclusion and Future Work -- References -- BSBM+: Extending BSBM to Evaluate Annotated RDF Features on Graph Databases -- 1 Introduction -- 2 Related Work -- 2.1 Annotated RDF -- 2.2 Benchmarks -- 2.3 Temporal and Geospatial Operators -- 3 Data Model -- 3.1 Annotation -- 3.2 Annotated RDF -- 3.3 Extended SPARQL and Extended Graph Engines -- 4 Benchmark Workflow -- 5 Dataset -- 5.1 Distribution of Annotation Type and Annotation Number -- 5.2 Distribution of the Annotation Values -- 6 Experiment -- 6.1 Metrics -- 6.2 Graph Engines Chosen and Experiment Circumstance -- 6.3 Engine Extension Module -- 6.4 SPARQL Extension Module -- 7 Results -- 7.1 Engine Extension Module -- 7.2 SPARQL Extension Module -- 8 Conclusion and Future Work -- References -- Detecting Spammers in Sina Micro-blog Based on Multiple Features -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Advertising Spammers Detecting Model -- 3.1 Basic Definitions -- 3.2 Similarity Detection -- 4 Experiment and Analysis on Dataset -- 4.1 Dataset and Preprocessing -- 4.2 Evaluation Criterion -- 5 Conclusions and Future Work -- References -- A Hybrid Method to Sentiment Analysis for Chinese Microblog -- 1 Introduction -- 2 Related Work -- 2.1 Lexicon-Based -- 2.2 Machine Leaning Method -- 3 A Hybrid Method to the Sentiment Analysis for Chinese Microblog (SAFCM) -- 3.1 Construction of Sentiment Lexicon -- 3.2 Word Embedding -- 3.3 Clustering -- 4 Experiments -- 4.1 Data Sets -- 4.2 Experiment Results. 327 $a5 Conclusion and Future Work -- References -- A User Personality-Similarity Model for Personalized Followee Recommendation in SINA Microblog -- 1 Introduction -- 2 Related Work -- 3 Our Method -- 3.1 User-Based Factor -- 3.2 Personality-Based Factors -- 4 Experiment -- 4.1 Results -- 5 Conclusions -- References -- CrowdGeoKG: Crowdsourced Geo-Knowledge Graph -- 1 Introduction -- 2 Technical Framework -- 2.1 Schema Design -- 2.2 Data Transformation and Linking -- 3 Dataset Exploitation -- 4 Conclusion and Future Work -- References -- Author Index. 330 $aThis book constitutes the refereed proceedings of the Second China Conference on Knowledge Graph and Semantic Computing, CCKS 2017, held in Chengdu, China, in August 2017. The 11 revised full papers and 6 revised short papers presented were carefully reviewed and selected from 85 submissions. The papers cover wide research fields including the knowledge graph, the Semantic Web, linked data, NLP, knowledge representation, graph databases. 410 0$aCommunications in Computer and Information Science,$x1865-0929 ;$v784 606 $aArtificial intelligence 606 $aData mining 606 $aDatabase management 606 $aInformation storage and retrieval 606 $aBig data 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aBig Data$3https://scigraph.springernature.com/ontologies/product-market-codes/I29120 615 0$aArtificial intelligence. 615 0$aData mining. 615 0$aDatabase management. 615 0$aInformation storage and retrieval. 615 0$aBig data. 615 14$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 615 24$aDatabase Management. 615 24$aInformation Storage and Retrieval. 615 24$aBig Data. 676 $a006.3 702 $aLi$b Juanzi$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aZhou$b Ming$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aQi$b Guilin$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aLao$b Ni$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRuan$b Tong$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDu$b Jianfeng$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910255453203321 996 $aKnowledge Graph and Semantic Computing. Language, Knowledge, and Intelligence$91896389 997 $aUNINA