{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:37:04Z","timestamp":1740202624310,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2004]]},"abstract":"<jats:p>Current approaches to word sense disambiguation use and combine various machine-learning techniques. Most refer to characteristics of the ambiguous word and surrounding words and are based on hundreds of examples. Unfortunately, developing large training sets is time-consuming. We investigate the use of symbolic knowledge to augment machine-learning techniques for small datasets. UMLS semantic types assigned to concepts found in the sentence and relationships between these semantic types form the knowledge base. A na&amp;iuml;ve Bayes classifier was trained for 15 words with 100 examples for each. The most frequent sense of a word served as the baseline. The effect of increasingly accurate symbolic knowledge was evaluated in eight experimental conditions. Performance was measured by accuracy based on 10-fold cross-validation. The best condition used only the semantic types of the words in the sentence. Accuracy was then on average 10% higher than the baseline; however, it varied from 8% deterioration to 29% improvement. In a follow-up evaluation, we noted a trend that the best disambiguation was found for words that were the least troublesome to the human evaluators.<\/jats:p>","DOI":"10.3233\/978-1-60750-949-3-381","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:29:25Z","timestamp":1740158965000},"source":"Crossref","is-referenced-by-count":0,"title":["Using Symbolic Knowledge in the UMLS to Disambiguate Words in Small Datasets with a Na&amp;iuml;ve Bayes Classifier."],"prefix":"10.3233","author":[{"family":"Leroy Gondy","sequence":"additional","affiliation":[]},{"family":"Rindflesch Thomas C.","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2004"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:42:12Z","timestamp":1740159732000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0926-9630&volume=107&spage=381"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2004]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-60750-949-3-381","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2004]]}}}