Preface
CICLing 2010 was the 11th Annual Conference on Intelligent Text Processing
and Computational Linguistics. The CICLing conferences provide a wide-scope
forum for discussion of the art and craft of natural language processing research
as well as the best practices in its applications.
This volume contains three invited papers and the regular papers accepted
for oral presentation at the conference. The papers accepted for poster presen-
tation were published in a special issue of another journal (see information on
the website). Since 2001, the proceedings of CICLing conferences have been pub-
lished in Springer’s Lecture Notes in Computer Science series, as volumes 2004,
2276, 2588, 2945, 3406, 3878, 4394, 4919, and 5449.
The volume is structured into 12 sections:
– Lexical Resources
– Syntax and Parsing
– Word Sense Disambiguation and Named Entity Recognition
– Semantics and Dialog
– Humor and Emotions
– Machine Translation and Multilingualism
– Information Extraction
– Information Retrieval
– Text Categorization and Classification
– Plagiarism Detection
– Text Summarization
– Speech Generation
The 2010 event received a record high number of submissions in the 11-
year history of the CICLing series. A total of 271 papers by 565 authors from 47
countries were submitted for evaluation by the International Program Committee
(see Tables 1 and 2). This volume contains revised versions of 61 papers, by 152
authors, selected for oral presentation; the acceptance rate was 23%.
The volume features invited papers by:
– Nicoletta Calzolari, Istituto di Linguistica Computazionale, Italy
– James Pustejovsky, Brandeis University, USA
– Shuly Wintner, University of Haifa, Israel
They presented excellent keynote lectures at the conference. Publication of ex-
tended full-text invited papers in the proceedings is a distinctive feature of the
CICLing conferences. What is more, in addition to presentation of their invited
papers, the keynote speakers organized separate lively informal events; this is
also a distinctive feature of this conference series.

Table of Contents XIX
Identification of Translationese: A Machine Learning Approach . . . . . . . . 503
Iustina Ilisei, Diana Inkpen, Gloria Corpas Pastor, and
Ruslan Mitkov
Information Extraction
Acquiring IE Patterns through Distributional Lexical Semantic
Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 512
Roberto Basili, Danilo Croce, Cristina Giannone, and Diego De Cao
Multi-view Bootstrapping for Relation Extraction by Exploring Web
Features and Linguistic Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 525
Yulan Yan, Haibo Li, Yutaka Matsuo, and Mitsuru Ishizuka
Sequential Patterns to Discover and Characterise Biological
Relations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537
Peggy Cellier, Thierry Charnois, and Marc Plantevit
Extraction of Genic Interactions with the Recursive Logical Theory of
an Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549
Alain-Pierre Manine, Erick Alphonse, and Philippe Bessie`res
Ontological Parsing of Encyclopedia Information . . . . . . . . . . . . . . . . . . . . . 564
Victor Bocharov, Lidia Pivovarova, Valery Rubashkin, and
Boris Chuprin
Information Retrieval
Selecting the N-Top Retrieval Result Lists for an Effective Data
Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 580
Antonio Jua´rez-Gonza´lez, Manuel Montes-y-Go´mez,
Luis Villasen˜or-Pineda, David Pinto-Avendan˜o, and
Manuel Pe´rez-Coutin˜o
Multi Word Term Queries for Focused Information Retrieval . . . . . . . . . . 590
Eric SanJuan and Fidelia Ibekwe-SanJuan
Optimal IR: How Far Away? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 602
Xiangdong An, Xiangji Huang, and Nick Cercone
Adaptive Term Weighting through Stochastic Optimization . . . . . . . . . . . 614
Michael Granitzer
Text Categorization and Classification
Enhancing Text Classification by Information Embedded in the Test
Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 627
Gabriela Ramı´rez-de-la-Rosa, Manuel Montes-y-Go´mez, and
Luis Villasen˜or-Pineda