EACL Reading

EACL 2009 accepted paper list is up. Here's my reading list:

WEAKLY SUPERVISED PART-OF-SPEECH TAGGING FOR RESOURCE-SCARCE LANGUAGES
Kazi Saidul Hasan and Vincent Ng

USING CYCLES AND QUASI-CYCLES TO DISAMBIGUATE DICTIONARY GLOSSES
Roberto Navigli

SYNTACTIC AND SEMANTIC KERNELS FOR SHORT TEXT PAIR CATEGORIZATION
Alessandro Moschitti

SENTIMENT SUMMARIZATION: EVALUATING AND LEARNING USER PREFERENCES
Kevin Lerman, Sasha Blair-Goldensohn and Ryan McDonald

PERSON IDENTIFICATION FROM TEXT AND SPEECH GENRE SAMPLES
Jade Goldstein-Stewart, Ransom Winder and Roberta Sabin

OUTCLASSING WIKIPEDIA IN OPEN-DOMAIN INFORMATION EXTRACTION: WEAKLY-SUPERVISED ACQUISITION OF ATTRIBUTES OVER CONCEPTUAL HIERARCHIES
Marius Pasca

GROWING FINELY-DISCRIMINATING TAXONOMIES FROM SEEDS OF VARYING QUALITY AND SIZE
Tony Veale, Guofu Li and Yanfen Hao

GENERATING A NON-ENGLISH SUBJECTIVITY LEXICON: RELATIONS THAT MATTER
Valentin Jijkoun and Katja Hofmann

CONTEXTUAL PHRASE-LEVEL POLARITY ANALYSIS USING LEXICAL AFFECT SCORING AND SYNTACTIC N-GRAMS
Apoorv Agarwal, Fadi Biadsy and Kathleen Mckeown

COMPANY-ORIENTED EXTRACTIVE SUMMARIZATION OF FINANCIAL NEWS
Katja Filippova, Mihai Surdeanu, Massimiliano Ciaramita and Hugo Zaragoza

ANALYSING WIKIPEDIA AND GOLD-STANDARD CORPORA FOR NER TRAINING
Joel Nothman, Tara Murphy and James R. Curran

And we're back ...

Sometime back I wrote about Wordle to visualize textual information using frequency counts. Change.gov, Obama's transition team website uses it on the comments in response to their health care system. This is very interesting but I think Wordle should display top 100 collocations instead of top 100 words. But oh, we also learnt at last ACL how to learn collocation information from unigram frequencies.