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Chapter 6. Inference beyond the index 2007 년 1 월 30 일 부산대학교 인공지능연구실 김민호 Text : FINDING OUT ABOUT Page. 182 ~ 251
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Introduce(1/4) - Knowledge representation AI is primary contribution to computer science! Related to: Programming language’s “abstract data types” Database (logical!) modeling -eg, ‘ontology’ building
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Introduce(2/4) - Traditionally (GOFAI) serving deductive goals Valid inference Man (x) -> Mortal(x) Man(Socrates) Mortal(Socrates) Expressiveness Even first-order logic offers tradeoffs wrt/propositional
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Introduce(3/4) - Machine learning: inductive sources of knowledge Data-mining Statistical analysis of large datasets Searching for patterns Inferring semantics (meaning) from syntactic cues from word statistics from bibliographic citations Even from capitalization -Proper names → Global reference!
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Introduce(4/4) - Exploiting other (non-index) information
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Subsection 6.1 Citation: Interdocument Links 6.2 Hypertext, Intradocument Links 6.3 Keyword Structures 6.4 Social Relations among Authors 6.5 Modes of Inference 6.6 Deep Interfaces 6.7 FOA(The Law) 6.8 FOA(Evolution) 6.9 Text-Based Inteligence
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6.1 Citation: Interdocument Links Citation is a pointer, from a document to a document. how accurately do we know the location of the citation in the citing paper? how precisely is its pointer into the cited paper?
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6.1 Citation: Interdocument Links Document similarity based on shared bibliographies Coupling Overlap between two document’s bibliographis Co-citation Degree to which two documents are both referenced by other document’s bibliographies
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6.1 Citation: Interdocument Links
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Common law depends on rule of precedence Stare decisis Prior decisions applied to new factual situations Hierarchical local jurisdictions limit interpretation Dialectic debate (rationale, justice, change, etc.) NB: Same corpus used by both adversaries References to history of O(10 year)
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6.1 Citation: Interdocument Links Unambiguous
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6.1 Citation: Interdocument Links Eigen-structure of citation graphs Authority: analogous to bibliometric ‘impact’ Hubs: Pull together authorities Citation-expanded hitlist
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Summary Writings do not exist in isolation Author explicit references to other’s documents provides excellent evidence concerning the ARGUMENTS they each make
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Google’s Page rank Simulate stationary distribution of Markov process with incremental update of page weight
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Hierarchic structure Visualizing references
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Pedagogical structure Prerequisite lattice Reading-level analysis – against well – tested vocabularies Level of coverage
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Argument relationships
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thesaurus BT/NT/RT relations aot / AI “ontologies”
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WordNet
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Classification taxonomies Institutionalized Myopic discipline focus
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Neural networks - basics Query Retrieval Relevance Feedback
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Construction of initial NNet
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Query: “Case-based approach to the law” Morphological processing of tokens High-frequency “noise” words elided
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SAS in IR Initial query may refer to many “features” Descriptive keywords are only one type Retrieval becomes a process of completion
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Type of relation less important than fact of association
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Initial retrieval
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Most highly ranked document
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Goal document
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3rd-order transitive associations
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4th-order transitive associations
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Swanson's Arrowsmith
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