Conceptual Grouping in Word Co-Occurrence Networks
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence. Machine Learning. Pages 694-700.
Abstract
Information Retrieval queries often result in a large number of documents found to be relevant. These documents are usually sorted by relevance, not by an analysis of what the user meant. If the document collection contains many documents on one of those meanings, it is hard to find other documents. We present a technique called conceptual grouping that automatically distinguishes between different meanings of a user query, given a document collection . By analysing a word cooccurrence network of a text database, we are able to form groups of words related to the query, grouped by semantic coherence. These groups are used to reorganise the results according to what the user has meant by his query. Testing shows that this automated technique can improve precision, help users find what they need more easily and give them a semantic overview of the document collection.
@inproceedings{ijcai1999p99,
title = {Conceptual Grouping in Word Co-Occurrence Networks},
author = {Veling, Anne and van der Weerd, Peter},
booktitle = {Proceedings of the Sixteenth International Joint Conference on
Artificial Intelligence, {IJCAI-99}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Thomas Dean},
pages = {694--700},
year = {1999},
note = {Machine Learning},
url = {https://ijcai.org/proceedings/1999/99},
}
TY - CPAPER TI - Conceptual Grouping in Word Co-Occurrence Networks AU - Veling, Anne AU - van der Weerd, Peter T2 - Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI-99 PB - International Joint Conferences on Artificial Intelligence PY - 1999 SP - 694 EP - 700 UR - https://ijcai.org/proceedings/1999/99 ER -Copied
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