TAILIEUCHUNG - Semantic based entity retrieval and disambiguation system for Twitter streams

Social media networks have evolved as a large repository of short documents and gives the greater challenges to effectively retrieve the content out of it. Many factors were involved in this process such as restricted length of a content, informal use of language (., slangs, abbreviations, styles, etc.) and low contextualization of the user generated content. To meet out the above stated problems, latest studies on context-based information searching have been developed and built on adding semantics to the user generated content into the existing knowledge base. And also, earlier, bag-of-concepts has been used to link the potential noun phrases into existing knowledge sources. Thus, in this paper, we have effectively utilized the relationships among the concepts and equivalence prevailing in the related concepts of the selected named entities by deriving the potential meaning of entities and find the semantic similarity between the named entities with three other potential sources of references (DBpedia, Anchor Texts and Twitter Trends). | Semantic based entity retrieval and disambiguation system for Twitter streams

• Báo chí - Truyền thông
• Semantic based entity retrieval
• Disambiguation system
• Twitter streams
• Vector space model
• Semantic similarity
• International Journal of Computer Science & Communication Networks
• Measuring semantic similarity between words
• Page counts and snippets
• Measuring semantic similarity
• Word co occurrence measures
• RDF Ontologies
• Semantic similarity between RDF ontologies
• Improvement in measuring the semantic similarity
• Framework of the R2Sim method
• Matching two RDF ontologies
• BMC Bioinformatics
• LncRNA functional similarity
• Disease semantic similarity
• lncRNA disease associations
• AUC values
• Sentence similarity
• Lexical semantic knowledge
• Syntactico semantic knowledge
• LMF ISO 24613
• Standardized dictionaries
• Verb Classification
• Distributional Similarity
• Syntactic and Semantic Structures
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Reducing semantic drift
• bagging and distributional similarity
• Tara McIntosh and James R
• Curran
• xử lý ngôn ngữ tự nhiên
• Learning to Grade Short Answer Questions
• Semantic Similarity Measures
• Dependency Graph Alignments
• Supersense Tagging
• Unknown Nouns
• mô hình ngôn ngữ
• Text to text Semantic Similarity
• Automatic Short Answer Grading
• Michael Mohler and Rada Mihalcea
• scientific reports
• model language
• process natural language
• Using lexical
• relational similarity
• semantic relations
• Word classification
• combined measures of distributional
• Gene ontology
• Semantic similarity measure
• Tree topology
• Biological process
• Molecular function
• Hierarchical clustering
• Least diverged human orthologs
• Deep learning for semantic matching
• Applied deep learning
• Describe important applications
• Semantic text similarity
• Schema/ontology matching
• Information content
• Information theory
• Biomedical ontologies
• Distributional based methods
• Disease associated gene
• Human phenotype ontology
• Random walk with restart algorithm
• Alzheimer’s disease
• Knowledge graph
• Machine learning
• Genetic programming
• Protein protein interaction prediction
• Drug disease associations
• Similarity constrained matrix factorization
• Low rank spaces
• Disease semantic information
• Semantic vector
• Word space model
• Random projection
• Apache Lucene
• Graduation Thesis
• Computer Science
• Implicit relational entity search
• Named Entity
• Semantic relation
• Similarity relation
• Vietnamese language domain
• Bag of visual word
• Deep learning
• Similarity measure
• Similar images
• Semantic based image retrieval
• Convolutional neural network
• Co Function network
• Gene function annotation
• Literature based discovery
• Indirect association
• Semantic relatedness
• Geographic information system