Using cause-effect relations in text to improve information retrieval precision

This study attempted to use semantic relations expressed in text, in partic ular cause-effect relations, to improve information retrieval effectiveness . The study investigated whether the information obtained by matching cause -effect relations expressed in documents with the cause-effect relations ex pressed in users queries can be used to improve document retrieval results. in comparison to using just keyword matching without considering relations . An automatic method for identifying and extracting cause-effect information in Wall Street Journal text was developed. Causal relation matching was fo und to yield a small but significant improvement in retrieval results when the weights used for combining the scores from different types of matching were customized for each query. Causal relation matching did not perform be tter than word proximity matching (i.e. matching pairs of causally related words in the query with pairs of words that co-occur within document senten ces), but the best results were obtained when causal relation matching was combined with word proximity matching. The best kind of causal relation mat ching was found to be one in which one member of the causal relation (eithe r the cause or the effect) was represented as a wildcard that could match w ith any word. (C) 2000 Elsevier Science Ltd. All rights reserved.