ABSTRACT Finding the Right Facts in the Crowd: Factoid Question Answering over Social Media (2009)
Community Question Answering has emerged as a popular and effective paradigm for a wide range of information needs. For example, to find out an obscure piece of trivia, it is now possible and even...
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...
Querying Large Text Databases for Efficient Information Extraction (2009)
Eugene Agichtein, Luis Gravano
A wealth of data is hidden within unstructured text. This data is often best exploited in structured or relational form, which is suited for sophisticated query processing, for integration with...
ABSTRACT Modeling Query-Based Access to Text Databases (2008)
Eugene Agichtein, Panagiotis Ipeirotis, Luis Gravano
Searchable text databases abound on the web. Applications that require access to such databases often resort to querying to extract relevant documents because of two main reasons. First, some text...
General Terms Algorithms, Measurement, Experimentation (2008)
We show that incorporating user behavior data can significantly improve ordering of top results in real web search setting. We examine alternatives for incorporating feedback into the ranking process...
Saurav Sahay, Baoli Li, Ernest V Garcia, Eugene Agichtein, Ashwin Ram
NLM's Unified Medical Language System (UMLS) is a very large ontology of biomedical and health data. In order to be used effectively for knowledge processing, it needs to be customized to a...
Question Answering over Implicitly Structured Web Content (2008)
Implicitly structured content on the Web such as HTML tables and lists can be extremely valuable for web search, question answering, and information retrieval, as the implicit structure in a page...
The top web search result is crucial for user satisfaction with the web search experience. We argue that the importance of the relevance at the top position necessitates special handling of the top...
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of web search users to...
Eugene Agichtein, Bill Gates, Ceo Microsoft, Bill Veghte, Vp Microsoft, Richard Stallman, ...
� “Unstructured ” text data is the primary source of human-generated information � Citeseer, comparison shopping, PIM systems, web search, data warehousing � Managing and utilizing text:...
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...
Eugene Agichtein, Carlos Castillo, Debora Donato, Aristides Gionis, Gilad Mishne, Eugene Agichtein, ...
ABSTRACT: The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability of such content increases, the task of identifying high-quality content in...
Pages 1–10 Extracting Synonymous Gene and Protein Terms from Biological Literature (2007)
Motivation: Genes and proteins are often associated with multiple names. More names are added as new functional or structural information is discovered. Because authors can use any one of the known...
Towards a Query Optimizer for Text-Centric Tasks (2007)
Ipeirotis, Panagiotis, Agichtein, Eugene, Jain, Pranay, Gravano, Luis
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured...
Towards a Query Optimizer for Text-Centric Tasks (2006)
Ipeirotis, Panagiotis G., Agichtein, Eugene, Jain, Pranay, Gravano, Luis
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured...
Towards a Query Optimizer for Text-Centric Tasks (2006)
Ipeirotis, Panagiotis G., Agichtein, Eugene, Jain, Pranay, Gravano, Luis
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured...
Towards a Query Optimizer for Text-Centric Tasks (2006)
Ipeirotis, Panagiotis G., Agichtein, Eugene, Jain, Pranay, Gravano, Luis
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured...
Towards a Query Optimizer for Text-Centric Tasks (2006)
Ipeirotis, Panagiotis G., Agichtein, Eugene, Jain, Pranay, Gravano, Luis
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured...
Panagiotis G. Ipeirotis, Eugene Agichtein, Luis Gravano, Pranay Jain
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured...
Scaling information extraction to large document collections (2005)
Information extraction and text mining applications are just beginning to tap the immense amounts of valuable textual information available online. In order to extract information from millions, and...
Web information extraction and user modeling: towards closing the gap (2005)
Web search engines have become the primary method of accessing information on the web. Billions of queries are submitted to major web search engines, reflecting a wide range of information needs....
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...
Scaling information extraction to large document collections (2005)
Information extraction and text mining applications are just beginning to tap the immense amounts of valuable textual information available online. In order to extract information from millions, and...
Eugene Agichtein, Luis Gravano, Snowball Extracting, Alfred V. Aho, Ravi Sethi, Rie Kubota Ando, ...
[10] Leonard E. Baum. An inequality and associated maximisation technique in statistical estimation for probabilistic functions of a Markov process. Inequalities, 3:1–8, 1972. Not sighted. [11]...
Learning to find answers to questions on the web (2004)
Eugene Agichtein, Steve Lawrence, Luis Gravano
We introduce a method for learning to find documents on the web that contain answers to a given natural language question. In our approach, questions are transformed into new queries aimed at...
Learning to find answers to questions on the web (2004)
Eugene Agichtein, Steve Lawrence, Luis Gravano
We introduce a method for learning to find documents on the web that contain answers to a given natural language question. In our approach, questions are transformed into new queries aimed at...
Learning to Find Answers to Questions (2004)
On The Web, Eugene Agichtein, Steve Lawrence, Luis Gravano
this article appeared as Agichtein et al. [2001]. The authors acknowledge the NEC Research Institute, where a substantial part of this research was accomplished, as well as support from the National...
Mining Reference Tables for Automatic Text Segmentation (2004)
Eugene Agichtein Columbia, Eugene Agichtein
Automatically segmenting unstructured text strings into structured records is necessary for importing the information contained in legacy sources and text collections into a data warehouse for...
Querying text databases for efficient information extraction (2003)
Eugene Agichtein, Luis Gravano
A wealth of information is hidden within unstructured text. This information is often best exploited in structured or relational form, which is suited for sophisticated query processing, for...
Modeling query-based access to text databases (2003)
Eugene Agichtein, Panagiotis Ipeirotis, Luis Gravano
Searchable text databases abound on the web. Applications that require access to such databases often resort to querying to extract relevant documents because of two main reasons. First, some text...
Modeling query-based access to text databases (2003)
Eugene Agichtein, Panagiotis Ipeirotis, Luis Gravano
Searchable text databases abound on the web. Applications that require access to such databases often resort to querying to extract relevant documents because of two main reasons. First, some text...
Extracting synonymous gene and protein terms from biological literature (2003)
Motivation: Genes and proteins are often associated with multiple names. More names are added as new functional or structural information is discovered. Because authors can use any one of the known...
Querying Large Text Databases for Efficient Information Extraction (2002)
Agichtein, Eugene, Gravano, Luis
A wealth of data is hidden within unstructured text. This data is often best exploited in structured or relational form, which is suited for sophisticated query processing, for integration with...
Learning Search Engine Specific Query Transformations for Question Answering (2001)
Agichtein, Eugene, Lawrence, Steve, Gravano, Luis
We introduce a method for learning query transformations that improves the ability to retrieve answers to questions from an information retrieval system. During the training stage the method involves...
Learning Search Engine Specific Query Transformations for Question Answering (2001)
We introduce a method for learning query transformations that improves the ability to retrieve answers to questions from an information retrieval system. During the training stage the method involves...
Learning Search Engine Specific Query Transformations for Question Answering (2001)
We introduce a method for learning query transformations that improves the ability to retrieve answers to questions from an information retrieval system. During the training stage the method involves...
Learning Search Engine Specific Query Transformations for Question Answering (2001)
Eugene Agichtein, Steve Lawrence, Luis Gravano
We introduce a method for learning query transformations that improves the ability to retrieve answers to questions from an information retrieval system. During the training stage the method involves...
Combining Strategies for Extracting Relations from Text Collections (2000)
Agichtein, Eugene, Eskin, Eleazar, Gravano, Luis
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering...
Combining Strategies for Extracting Relations from Text Collections (2000)
Eugene Agichtein, Eleazar Eskin, Luis Gravano
Abstract Text documents often contain valuable structured datathat is hidden in regular English sentences. This data is best exploited if available as a relational table that wecould use for...
Combining Strategies for Extracting Relations from Text Collections (2000)
Eugene Agichtein Eleazar, Eugene Agichtein, Eleazar Eskin, Luis Gravano
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering...
Combining Strategies for Extracting Relations from Text Collections (2000)
Eugene Agichtein, Eleazar Eskin, Luis Gravano
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering...
Snowball: Extracting Relations from Large Plain-Text Collections (2000)
Eugene Agichtein, Luis Gravano
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering...
Combining Strategies for Extracting Relations from Text Collections (2000)
Eugene Agichtein, Eleazar Eskin, Luis Gravano
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering...
Combining Strategies for Extracting Relations from Text Collections (2000)
Eugene Agichtein, Eleazar Eskin, Luis Gravano
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering...
Extracting Relations from Large Plain-Text Collections (1999)
Agichtein, Eugene, Gravano, Luis
Text documents often contain valuable structured data thatis hidden in regular English sentences. This data is best exploited ifavailable as a relational table that we could use for answering precise...
NYU: Description of the MENE Named Entity System as Used in MUC-7 (1998)
Andrew Borthwick, John Sterling, Eugene Agichtein, Ralph Grishman
Exploiting Diverse Knowledge Sources via Maximum Entropy in Named Entity Recognition (1998)
Andrew Borthwick, John Sterling, Eugene Agichtein, Ralph Grishman
This paper describes a novel statistical named-entity (i.e. "proper name") recognition system built around a maximum entity framework. By work-ing v,ithin the framework of maximum...