Chapter 6. Inference beyond the index

2007 년 1 월 30 일부산대학교 인공지능연구실 김민호

Text : FINDING OUT ABOUTPage. 182 ~ 251

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

Introduce(2/4) - Traditionally (GOFAI) serving deductive goals

Valid inferenceMan (x) -> Mortal(x)

Man(Socrates)

Mortal(Socrates) Expressiveness

Even first-order logic offers tradeoffs wrt/propositional

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!

Introduce(4/4) - Exploiting other (non-index) information

Subsection

6.1 Citation: Interdocument Links6.2 Hypertext, Intradocument Links6.3 Keyword Structures6.4 Social Relations among Authors6.5 Modes of Inference6.6 Deep Interfaces6.7 FOA(The Law)6.8 FOA(Evolution)6.9 Text-Based Inteligence

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?

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

6.1 Citation: Interdocument Links

6.1 Citation: Interdocument Links

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)

6.1 Citation: Interdocument Links

Unambiguous

6.1 Citation: Interdocument Links

Eigen-structure of citation graphs

Authority: analogous to bibliometric ‘impact’

Hubs: Pull together authorities Citation-expanded hitlist

Summary

Writings do not exist in isolation Author explicit references to other’s documents

provides excellent evidence concerning the ARGUMENTS they each make

Google’s Page rank

Simulate stationary distribution of Markov process with incremental update of page weight

Hierarchic structure

Visualizing references

Pedagogical structure

Prerequisite lattice Reading-level analysis – against well – tested

vocabularies Level of coverage

Argument relationships

thesaurus

BT/NT/RT relations aot / AI “ontologies”

WordNet

Classification taxonomies

Institutionalized Myopic discipline

focus

Neural networks - basicsQuery

Retrieval Relevance

Feedback

Construction of initial NNet

Query: “Case-based approach to the law”

Morphological processing of tokens High-frequency “noise” words elided

SAS in IR

Initial query may refer to many “features” Descriptive keywords are

only one type Retrieval becomes a

process of completion

Type of relation less important than fact of association

Initial retrieval

Most highly ranked document

Goal document

3rd-order transitive associations

4th-order transitive associations

Swanson's Arrowsmith