Entity Recognition (ER) is a key component of relation extraction systems and many other natural-language processing applications. Unfortunately, most ER systems are restricted to...
One popular form of semantic search observed in several modern search engines is to recognize query patterns that trigger instant answers or domain-specific search, producing sem...
We propose a novel method to automatically acquire a term-frequency-based taxonomy from a corpus using an unsupervised method. A term-frequency-based taxonomy is useful for applic...
Karin Murthy, Tanveer A. Faruquie, L. Venkata Subr...
We present an unsupervised method for detecting grammatical errors by inferring negative evidence from edited textual corpora. The system was developed and tested using essay-leng...
The advent of digital libraries along with the tremendous growth of digital content call for distributed and scalable approaches for managing vast data collections. Peer-to-peer (P...
Previous work by Pedersen, Purandare and Kulkarni (2005) has resulted in an unsupervised method of name discrimination that represents the context in which an ambiguous name occurs...
Abstract. We present a novel, simple, unsupervised method for characterizing the semantic relations that hold between nouns in noun-noun compounds. The main idea is to discover pre...
One of the most important steps in text processing and information retrieval is stemming—reducing of words to stems expressing their base meaning, e.g., bake, baked, bakes, bakin...
Alexander F. Gelbukh, Mikhail Alexandrov, Sang-Yon...
We describe an unsupervised method to segment objects detected in images using a novel variant of an interest point template, which is very efficient to train and evaluate. Once a...
Himanshu Arora, Nicolas Loeff, David A. Forsyth, N...