Entity Recognition and Relation Extraction. Categories and Subject Descriptors (2009)
H. [information Storage, Eugene Agichtein, Silviu Cucerzan
Exploiting lexical and semantic relationships in text can dramatically improve information retrieval accuracy. Most notably, named entities and relations between entities are crucial for effective...
Leveraging Popular Destinations to Enhance Web Search Interaction* (2008)
Ryen W. White, Mikhail Bilenko, Silviu Cucerzan
This article presents a novel Web search interaction feature that for a given query provides links to Web sites frequently visited by other users with similar information needs. These popular...
Network Flow for Collaborative Ranking (2008)
Ziming Zhuang, Silviu Cucerzan, C. Lee Giles
Abstract: In query based Web search, a significant percentage of user queries are underspecified, most likely by naive users. Collaborative ranking helps the naive user by exploiting the collective...
Network Flow for Collaborative Ranking (2008)
Ziming Zhuang, Silviu Cucerzan, C. Lee Giles
Abstract. In query based Web search, a significant percentage of user queries are underspecified, most likely by naive users. Collaborative ranking helps the naive user by exploiting the collective...
Factoid Question Answering over Unstructured and Structured Web Content (2008)
Silviu Cucerzan, Eugene Agichtein
We describe our experience with two new, builtfrom -scratch, web-based question answering systems applied to the TREC 2005 Main Question Answering task, which use complementary models of answering...
Language Independent NER using a Unified Model of Internal and Contextual Evidence (2007)
Cucerzan, Silviu, Yarowsky, David
Abstract This paper investigates the use of a language independent model for named entity recognition based on iterative learning in a co-training fashion, using word-internal and contextual...
Bootstrapping a Multilingual Part-of-speech Tagger in One Person-day (2007)
Cucerzan, Silviu, Yarowsky, David
This paper presents a method for bootstrapping a fine-grained, broad-coverage part-of-speech (POS) tagger in a new language using only one person day of data acquisition effort. It requires only...
Large-scale named entity disambiguation based on Wikipedia data (2007)
This paper presents a large-scale system for the recognition and semantic disambiguation of named entities based on information extracted from a large encyclopedic collection and Web search results....
Large-scale named entity disambiguation based on Wikipedia data (2007)
This paper presents a large-scale system for the recognition and semantic disambiguation of named entities based on information extracted from a large encyclopedic collection and Web search results....
Network Flow for Collaborative Ranking (2006)
Ziming Zhuang, Silviu Cucerzan, C. Lee Giles
In query based Web search, a significant percentage of user queries are underspecified, most likely by naive users. Collaborative ranking helps the naive user by exploiting the collective expertise....
Predicting Accuracy of Extracting Information from Unstructured Text Collections (2005)
Eugene Agichtein, Silviu Cucerzan
Exploiting lexical and semantic relationships in large unstructured text collections can significantly enhance managing, integrating, and querying information locked in unstructured text. Most...
Bootstrapping a Multilingual Part-of-speech Tagger in One Person-day (2002)
Silviu Cucerzan, David Yarowsky
This paper presents a method for bootstrapping a fine-grained, broad-coverage part-of-speech (POS) tagger in a new language using only one personday of data acquisition effort. It requires only three...
Language Independent NER using a Unified Model of Internal and (2002)
Contextual Evidence Silviu, Silviu Cucerzan, David Yarowsky
This paper investigates the use of a language independent model for named entity recognition based on iterative learning in a co-training fashion, using word-internal and contextual information as...
Combining classifiers for word sense disambiguation (2002)
Radu Florian, Silviu Cucerzan, Charles Schafer
Classifier combination is an e#ective and broadly useful method of improving system performance. This article investigates in depth a large number of both well-established and novel classifier...
Bootstrapping a Multilingual Part-of-speech Tagger (2002)
Silviu Cucerzan, David Yarowsky
This paper presents a method for bootstrapping a fine-grained, broad-coverage part-of-speech (POS) tagger in a new language using only one personday of data acquisition effort. It requires only three...
The Johns Hopkins SENSEVAL2 system descriptions (2001)
David Yarowsky, Silviu Cucerzan, Radu Florian, Charles Schafer, Richard Wicentowski
This article describes the Johns Hopkins University (JHU) sense-disambiguation systems that participated in seven SENSEVAL2 tasks: four supervised lexical choice systems (Basque, English, Spanish,...
Language independent minimally supervised induction of lexical probabilities (2000)
Silviu Cucerzan, David Yarowsky
A central problem in part-of-speech tagging, especially for new languages for which limited annotated resources are available, is estimating the distribution of lexical probabilities for unknown...
Language independent minimally supervised induction of lexical probabilities (2000)
Silviu Cucerzan, David Yarowsky
A central problem in part-of-speech tagging, especially for new languages for which limited annotated resources are available, is estimating the distribution of lexical probabilities for unknown...
Language independent named entity recognition combining morphological and contextual evidence (1999)
Silviu Cucerzan, David Yarowsky
Identifying and classifying personal, geographic, institutional or other names in a text is an important task for numerous applications. This paper describes and evaluates a language-independent...
Language Independent NER Using a Unified Model of Internal and Contextual Evidence
Silviu Cucerzan, David Yarowsky
This paper investigates the use of a language independent model for named entity recognition based on iterative learning in a co-training fashion, using word-internal and contextual information as...