PPT-Distributional Semantic Models

in Lexical Typology Constructing a typological questionnaire Daria Ryzhova School of Linguistics NRU HSE Outline Lexical Typology Framebased Approach Ideology Typological questionnaire. se 1 Introduction Distributional approaches to meaning acquisition utilize distributional proper ties of linguistic entities as the building blocks of semantics In doing so they rely fundamentally on a set of assumptions about the nature of language Semantic networks - history. Network notations are almost as old as logic. Porphyry (3rd century AD) – tree-based hierarchies to describe Aristotle’s categories. Frege (1879) - concept writing, a tree notation for the first complete version of first-order logic . . 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. Prof. O. . Nierstrasz. Thanks to Jens . Palsberg. and Tony Hosking for their kind permission to reuse and adapt the CS132 and CS502 lecture notes.. http://www.cs.ucla.edu/~palsberg/. http://www.cs.purdue.edu/homes/hosking/. １２月７日. 研究会. 祭都援炉. (. マットエンロ. ). Up until now: Getting to know NLP. “Speech and Language Processing” (. Jurafsky. & Martin). 論文：. On-Demand Information Extract . Verbs of Falling and Beyond. Katia. . Rakhilina. (NRU HSE, Moscow). “. Verbs, verb phrases and verbal categories”. 23-25 March. Hebrew University of Jerusalem. BEYOND:. Lexical Typology. Main objectives. 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 . Word Association and Similarity. Ido Dagan. Including Slides by:. . Katrin. Erk (mostly), Marco Baroni,. Alessandro Lenci (BLESS). 2. Word Association Measures. Goal: measure the statistical strength of word (term) co-occurrence in corpus. 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. Katrin . Erk. You can get an idea of what a word means from observing it in context. He filled the . wampimuk. , passed it around, and we all drank some. We found a little hairy . wampimuk. . sleeping behind a tree. . Notable Opinions. . 1. . The . success of . equivalent . effect is . ‘. illusory’. 2. The . most crucial problem in . translation theory . and practice will always be:. ‘the conflict of loyalties’ and. Omer Levy. . Ido. Dagan. Bar-. Ilan. University. Israel. Steffen Remus Chris . Biemann. Technische. . Universität. Darmstadt. Germany. Lexical Inference. Lexical Inference: Task Definition. Movement led by W3C that promotes common formats for data on the web. Describes things in a way that computer applications can understand it. Describes the relationship between things and properties of things.