A Comparison of Machine Measures of Text Document Similarity with Human Judgments

@misc{citeulike:1230941, abstract = {A central problem in the information sciences involves measuring the semantic similarity between text documents. Although this is fundamentally a cognitive modeling problem, existing methods have not been assessed in terms of their ability to emulate human judgments of similarity. To address this problem, we conducted a controlled psychological experiment that collected repeated similarity measures for each pair of documents in a small corpus of short news documents. We then considered...}, author = {Lee, Michael D. and Pincombe, Brandon and Welsh, Matthew }, citeulike-article-id = {1230941}, keywords = {clustering, latent\_semantic\_indexing, lsi, pair\_project, similarity, vector\_space}, posted-at = {2008-06-24 23:08:04}, priority = {2}, title = {A Comparison of Machine Measures of Text Document Similarity with Human Judgments}, url = {http://citeseer.ist.psu.edu/647941.html} }

TY - GEN ID - citeulike:1230941 L3 - citeulike-article-id:1230941 TI - A Comparison of Machine Measures of Text Document Similarity with Human Judgments N2 - A central problem in the information sciences involves measuring the semantic similarity between text documents. Although this is fundamentally a cognitive modeling problem, existing methods have not been assessed in terms of their ability to emulate human judgments of similarity. To address this problem, we conducted a controlled psychological experiment that collected repeated similarity measures for each pair of documents in a small corpus of short news documents. We then considered... KW - clustering KW - latent_semantic_indexing KW - lsi KW - pair_project KW - similarity KW - vector_space AU - Lee, Michael AU - Pincombe, Brandon AU - Welsh, Matthew UR - http://citeseer.ist.psu.edu/647941.html ER -