PPT-5. Semantic Analysis

Prof O Nierstrasz Thanks to Jens Palsberg and Tony Hosking for their kind permission to reuse and adapt the CS132 and CS502 lecture notes httpwwwcsuclaedupalsberg httpwwwcspurdueeduhomeshosking. Semantic Role Labeling. Introduction. Semantic Role Labeling. Agent. Theme. Predicate. Location. Can we figure out that these have the same meaning?. XYZ . corporation . bought. the . stock.. They . . Multi-label Protein Subcellular Localization. Shibiao WAN and Man-Wai MAK. The Hong Kong Polytechnic University. Sun-Yuan KUNG. Princeton University. Outline. Introduction and Motivation. Retrieval of GO Terms. Module 1 - . Part . 1. The . Semantic Web and Linked Data . Concepts: . A . basic overview . . 1-. 1. Library of . Congress. BIBFRAME Pilot Training . for Catalogers. Overview. Context . Goals . of the . -concepts and facts. -several similar models describe . the organization . of semantic . memory. 1) Collins & . Quillian’s. Hierarchical Network Model. -nodes to represent individual items, ideas, organized hierarchically. Katrin Erk. University of Texas at . Austin. Meaning in Context Symposium. München. September 2015. Joint work with Gemma . Boleda. Semantic features by example: . Katz & Fodor. Different meanings of a word characterized by lists of semantic features. . P . L . Chandrika. . . Advisors: Dr.. . C. V. Jawahar . . . Centre for Visual Information Technology, IIIT- Hyderabad. Problem Setting . Dominic Oldman. Peter . Haase. Creating the Cultural Heritage Knowledge Graph. ResearchSpace. Project. Goals and context. ResearchSpace. Platform. m. etaphacts. Knowledge Graph Platform. Brief demo. 4. th. . International Conf. on Biomedical . Ontology . ICBO 2013. 9. th. . Data Integration in Life Science . DILS 2013. 4. th. . Canadian Semantic Web Conference . CSWS 2013. July 2013 at Concordia University in . In the Context of the ETC Project. SAW Intro. Wiki. Users collaboratively develop and organize content. Information Analysis is up to the user. Goal: . “Self-aware wiki that can develop and organize its content. Towards Bridging Semantic Gap and Intention Gap in Image Retrieval. Hanwang. Zhang. 1. , . Zheng. -Jun Zha. 2. , Yang Yang. 1. , . Shuicheng. Yan. 1. , . Yue. Gao. 1. , Tat-. Seng. Chua. 1. 1: National University of Singapore. Nikhil . Rasiwasia. , . Nuno. . Vasconcelos. Statistical Visual Computing Laboratory. University of California, San Diego. Thesis Defense. Ill pause for a few moments so that you all can finish reading this. . Ivan Rygaev. Laboratory of Computational Linguistics. Kharkevich Institute for Information Transmission Problems RAS, Moscow, Russia. RuleML RR. London, July 2017. 1. Rule-based Reasoning in Semantic Text Analysis. Review. So far, we’ve covered the following: . . Compilation methods: compilation vs. interpretation.. . The overall . c. ompilation process.. Front-end analysis . Lexical Analysis. Syntax Analysis. Introduction. Semantic Role Labeling. Agent. Theme. Predicate. Location. Can we figure out that these have the same meaning?. XYZ . corporation . bought. the . stock.. They . sold. the stock to XYZ .