Victor Lavrenko


2015

pdf bib
Sampling Techniques for Streaming Cross Document Coreference Resolution
Luke Shrimpton | Victor Lavrenko | Miles Osborne
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

pdf bib
Twitter-scale New Event Detection via K-term Hashing
Dominik Wurzer | Victor Lavrenko | Miles Osborne
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing

pdf bib
Tracking unbounded Topic Streams
Dominik Wurzer | Victor Lavrenko | Miles Osborne
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

2014

pdf bib
Query-by-Example Image Retrieval using Visual Dependency Representations
Desmond Elliott | Victor Lavrenko | Frank Keller
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

2013

pdf bib
Variable Bit Quantisation for LSH
Sean Moran | Victor Lavrenko | Miles Osborne
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2012

pdf bib
The BladeMistress Corpus: From Talk to Action in Virtual Worlds
Anton Leuski | Carsten Eickhoff | James Ganis | Victor Lavrenko
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

Virtual Worlds (VW) are online environments where people come together to interact and perform various tasks. The chat transcripts of interactions in VWs pose unique opportunities and challenges for language analysis: Firstly, the language of the transcripts is very brief, informal, and task-oriented. Secondly, in addition to chat, a VW system records users' in-world activities. Such a record could allow us to analyze how the language of interactions is linked to the users actions. For example, we can make the language analysis of the users dialogues more effective by taking into account the context of the corresponding action or we can predict or detect users actions by analyzing the content of conversations. Thirdly, a joined analysis of both the language and the actions would empower us to build effective modes of the users and their behavior. In this paper we present a corpus constructed from logs from an online multiplayer game BladeMistress. We describe the original logs, annotations that we created on the data, and summarize some of the experiments.

pdf bib
Using paraphrases for improving first story detection in news and Twitter
Saša Petrović | Miles Osborne | Victor Lavrenko
Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2010

pdf bib
The Edinburgh Twitter Corpus
Saša Petrović | Miles Osborne | Victor Lavrenko
Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media

pdf bib
Streaming First Story Detection with application to Twitter
Saša Petrović | Miles Osborne | Victor Lavrenko
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

2007

pdf bib
Information Retrieval On Empty Fields
Victor Lavrenko | Xing Yi | James Allan
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference

2006

pdf bib
Sentiment Retrieval using Generative Models
Koji Eguchi | Victor Lavrenko
Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing

2001

pdf bib
Monitoring the News: a TDT demonstration system
David Frey | Rahul Gupta | Vikas Khandelwal | Victor Lavrenko | Anton Leuski | James Allan
Proceedings of the First International Conference on Human Language Technology Research