Concept Description Vectors and the 20 Questions Game Włodzisław Duch Tomasz Sarnatowicz Julian Szymański

Permanent container for general knowledge Semantic Memory Permanent container for general knowledge

Hierarchical Model Collins & Quillian, 1969

Semantic network Collins & Loftus, 1975

Semantic Memory

All the concepts and keywords create a Semantic Space All the concepts and keywords create a semantic matrix

Concept Description Vectors CDV – a vector of properties describing a single concept Most of elements are 0’s – sparse vector

Data Sources I Machine readable dictionaries and ontologies: Wordnet ConceptNet Sumo/Milo ontology

Data Sources II Dictionaries data retrieval On-line sources Approach Merriam Webster Wordnet (gloss) MSN Encarta Approach Word morphing Phrases extraction (with POS tagger) Statistical analysis

Data access Binary dictionary search 220 = 1048576 Binary search – not acceptable in complex semantical applications Narrowing concept space by subsequent queries

20 Questions Game Algorithm p(keyword=vi) is fraction of concepts for which the keyword has value vi Candidate concepts O(A) are selected according to: O(A) = {i; |CDVi-A| is minimal} where CDVi is a vector for concept i and A is a partial vector of retrieved answers

Word puzzles 20Q game reversed Concept – known Keywords – the ones that would lead to the concept