In this paper, we propose a linear model-based general framework to combine k-best parse outputs from multiple parsers. The proposed framework leverages on the strengths of previo...
Statistical bilingual word alignment has been well studied in the context of machine translation. This paper adapts the bilingual word alignment algorithm to monolingual scenario ...
Distinguishing speculative statements from factual ones is important for most biomedical text mining applications. We introduce an approach which is based on solving two sub-probl...
In this paper we investigate temporal patterns of web search queries. We carry out several evaluations to analyze the properties of temporal profiles of queries, revealing promisi...
Enrique Alfonseca, Massimiliano Ciaramita, Keith H...
One of the most desired information types when planning a trip to some place is the knowledge of transport, roads and geographical connectedness of prominent sites in this place. ...
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...
Named entity disambiguation concerns linking a potentially ambiguous mention of named entity in text to an unambiguous identifier in a standard database. One approach to this task...
Automated mining of novel documents or sentences from chronologically ordered documents or sentences is an open challenge in text mining. In this paper, we describe the preprocess...
Word sense disambiguation is typically phrased as the task of labeling a word in context with the best-fitting sense from a sense inventory such as WordNet. While questions have o...