词义消歧算法与应用

导读
contributors
foreword
preface
1 introduction
eneko agirre and philip edmonds
1。1 word sense disambiguation
1。2 a brief history of wsd research
1。3 what is a word sense?
1。4 applications of wsd
1。5 basic approaches to wsd
1。6 state-of-the-art performance
1。7 promising directions
1。8 overview of this bok
1。9 further reading
references

2 word senses
adam kilgarriff
2。1 introduction
2。2 lexicographers
2。3 philosophy
2。3。1 meaning is something you do
2。3。2 the fregean tradition and reification
2。3。3 two incompatible semantics?
2。3。4 implications for word senses
2。4 lexicalization
2。5 corpus evidence
2。5。1 lexicon size
2。5。2 quotations
2。6 conclusion
2。7 further reading
acknowledgments
references

3 making sense about sense
nancy ide and yorick wilks
3。1 introduction
3。2 wsd and the lexicographers
3。3 wsd and sense inventories
3。4 nlp applications and wsd
3。5 what level of sense distinctions do we need for nlp, if any?
3。6 what now for wsd?
3。7 conclusion
references

4 evaluation of wsd systems
martha palmer, hwee tou ng and hoa trang dang
4。1 introduction
4。1。1 terminology
4。1。2 overview
4。2 background
4。2。1 wordnet and semcor
4。2。2 the line and interest corpora
4。2。3 the dso corpus
4。2。4 open mind word expert
4。3 evaluation using pseudo-words
4。4 senseval evaluation exercises
4。4。1 senseval-1
evaluation and scoring
4。4。2 senseval-2
english all-words task
english lexical sample task
4。4。3 comparison of tagging exercises
4。5 sources of inter-annotator disagreement
4。6 granularity of sense: groupings for wordnet
4。6。1 criteria for wordnet sense grouping
4。6。2 analysis of sense grouping
4。7 senseval-3
4。8 discussion
references

5 knowledge-based methods for wsd
rada mihalcea
5。1 introduction
5。2 lesk algorithm
5。2。1 variations of the lesk algorithm
simulated annealing
simplified lesk algorithm
augmented semantic spaces
summary
5。3 semantic similarity
5。3。1 measures of semantic similarity
5。3。2 using semantic similarity within a local context
5。3。3 using semantic similarity within a global context
5。4 selectional preferences
5。4。1 preliminaries: learning word-to-word relations
5。4。2 learning selectional preferences
5。4。3 using selectional preferences
5。5 heuristics for word sense disambiguation
5。5。1 most frequent sense
5。5。2 one sense per discourse
5。5。3 one sense per collocation
5。6 knowledge-based methods at senseval-2
5。7 conclusions
references

6 unsupervised corpus-based methods for wsd
ted pedersen
6。1 introduction
6。1。1 scope
6。1。2 motivation
distributional methods
translational equivalence
6。1。3 approaches
6。2 type-based discrimination
6。2。1 representation of context
6。2。2 algorithms
latent semantic analysis （lsa）
hyperspace analogue to language （hal）
clustering by committee （cbc）
6。2。3 discussion
6。3 token-based discrimination
6。3。1 representation of context
6。3。2 algorithms
context group discrimination
mcquitty's similarity analysis
6。3。3 discussion
6。4 translational equivalence
6。4。1 representation of context
6。4。2 algorithms
6。4。3 discussion
6。5 conclusions and the way forward
acknowledgments
references

7 supervised corpus-based methods for wsd
8 knowledge sources for wsd
9 automatic acquisition of lexical information and examples
10 domain-specific wsd
11 wsd in nlp applications