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.

Too many cooks?

Computational Linguistics is becoming like the Science or Nature. For instance, see this paper in the current issue: (In this case, the broth wasn't spoiled ;-)

Guess which paper has the largest number of authors on the ACL anthology?

To theory or not to theory

I stumbled upon this paper "Reflections after Refereeing Papers for NIPS" by Leo Breiman that gives some really candid insights into theory papers. (Unfortunately, I could not find a soft copy to share, except this link.) Some noteworthy observations:

"No theorems" implies "No theory"

"... more than 99% of the published papers are useless exercises."

"Mathematical theory is not critical to development of machine learning."

"Our fields would be better off with far fewer theorems, less emphasis on faddish stuff, and much more into scientific inquiry and engineering."

I really liked this article, especially coming from someone who has been working in theory all his life but I would still prefer reading papers giving theoretical insight, however useless, than pages and pages of feature engineering & experimentation using classifier X on problem Y -- the current trend at ACL.

A quick scan at ACL

Mendicant Bug informs about a new tag-cloud service called Wordle. Here is a look at this year's ACL. Gives a clear idea of what is going on! A larger image is available here.

Powerset Natural Language Search

Powerset, a company we only remember seeing as conference sponsors, now actually has something working. After receiving an email from them, I tried out several queries. At best, it seems to answer most Wh-questions and certain whole-part relations.

Try out the same query on Google.

Writing style

The sweetest thing ever written in a paper: "The reader who is unfamiliar with this field or who has allowed his or her facility with some of its concepts to fall into disrepair may profit from a brief perusal of Feller (1950) and Gallagher (1968)."

- Brown et. al., "Class based n-gram Models of Natural Language.", Computational Linguistics, 1990

Searching ACL anthology

If you are looking up the ACL anthology regularly, my friend Markus has a nice firefox search plugin to do that. You can get that and others from this page.

ACL accepted papers

Hal posted a while back about the ACL accepted papers that I just read now -- I've been living under a rock for some time. You can get a printer friendly version here. I know, my paper did not make it to that list :(

New additions to my reading list:

Distributional Identification of Non-Referential Pronouns
Shane Bergsma, Dekang Lin and Randy Goebel

An Unsupervised Approach to Biography Production using Wikipedia
Fadi Biadsy, Julia Hirschberg and Elena Filatova

Resolving Personal Names in Email Using Context Expansion
Tamer Elsayed, Douglas Oard and Galileo Namata

Mining Wiki Resources for Multilingual Named Entity Recognition
Alexander Richman and Patrick Schone

Inducing Gazetteers for Named Entity Recognition by Large-scale Clustering of Dependency Relations
Jun'ichi Kazama and Kentaro Torisawa

Name Translation in Statistical Machine Translation - Learning When to Transliterate
Ulf Hermjakob, Kevin Knight and Hal Daume



The Tradeoffs Between Open and Traditional Relation Extraction
Michele Banko and Oren Etzioni

(Longest paper title)
Unsupervised Discovery of Generic Relationships Using Pattern Clusters and its Evaluation by Automatically Generated SAT Analogy Questions
Dmitry Davidov and Ari Rappoport

Finding Contradictions in Text
Marie-Catherine de Marneffe, Anna Rafferty and Christopher Manning

Extracting Question-Context-Answer Triples from Online Forums
Shilin Ding, Gao Cong, Chin-Yew Lin and Xiaoyan Zhu

EM Can Find Pretty Good HMM POS-Taggers (When Given a Good Start)
Yoav Goldberg, Meni Adler and Michael Elhadad

Extraction of Entailed Semantic Relations Through Syntax-based Comma Resolution
Vivek Srikumar, Roi Reichart, Mark Sammons, Ari Rappoport and Dan Roth

Learning Bigrams from Unigrams
Xiaojin Zhu, Andrew Goldberg, Michael Rabbat and Robert Nowak

Evaluating Roget's Thesauri
Alistair Kennedy and Stan Szpakowicz

Randomized Language Models via Perfect Hash Functions
David Talbot and Thorsten Brants

Solving Relational Similarity Problems Using the Web as a Corpus
Preslav Nakov and Marti Hearst

What do you do?

As a grad student working on NLP how do you explain what you are working on, to friends and family? I inevitably end up referring to the Google search engine even though what I do is quite far from IR. Actually, thats not true. These days IR seems to consume everything but thats another story.

This reminds me of a funny conversation at CLSP recently:

Sanjeev is telling us about an incident where a concerned parent of a young child with a speaking disability is asking him for his opinion. Apparently, she is confused about "Language and Speech Processing" in CLSP.

Keith butts in: "Run a few more iterations of EM and he'll be fine."

A song on parsing

We all know Jason's love for parsing from his work but it takes a different level of dedication to write a Valentine's Day song about parsing.

As Jason says, "Parsers just want to be appreciated, like everyone else."