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Exploring Semantic Memory: The 20 Questions Game and Concept-Description Vectors

This document delves into the intersection of semantic memory and the 20 Questions game, elucidating how concepts and their properties can be modeled using concept-description vectors. It references the foundational theoretical models of Collins and Quillian (1969) and Collins and Loftus (1975), describing a hierarchical structure to visualize knowledge as a semantic network. The paper discusses data sources like Wordnet and ontologies, and methodologies for concept extraction, including word morphing and statistical analysis, to enhance semantic access and retrieval.

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Exploring Semantic Memory: The 20 Questions Game and Concept-Description Vectors

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

  2. Semantic Memory Permanent container for general knowledge

  3. Hierarchical Model Collins & Quillian, 1969

  4. Semantic network Collins & Loftus, 1975

  5. Semantic Memory

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

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

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

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

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

  11. 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

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

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