4 papers
Coupled Clustering: a Method for Detecting Structural Correspondence
Zvika Marx, Ido Dagan, Joachim Buhmann
This paper proposes a new paradigm and computational framework for identification of correspondences between sub-structures of distinct composite systems. For this, we define and i…
Detecting Sub-Topic Correspondence through Bipartite Term Clustering
Zvika Marx, Ido Dagan, Eli Shamir
This paper addresses a novel task of detecting sub-topic correspondence in a pair of text fragments, enhancing common notions of text similarity. This task is addressed by coupling…
Similarity-Based Models of Word Cooccurrence Probabilities
Ido Dagan, Lillian Lee, Fernando C. N. Pereira
In many applications of natural language processing (NLP) it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may need to dete…
A Memory-Based Approach to Learning Shallow Natural Language Patterns
Shlomo Argamon, Ido Dagan, Yuval Krymolowski
Recognizing shallow linguistic patterns, such as basic syntactic relationships between words, is a common task in applied natural language and text processing. The common practice…