{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T04:34:21Z","timestamp":1649133261153},"reference-count":13,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[2008,6]]},"abstract":"<jats:p> This paper describes the use of two machine learning techniques, naive Bayes and decision trees, to address the task of assigning function tags to nodes in a syntactic parse tree. Function tags are extra functional information, such as logical subject or predicate, that can be added to certain nodes in syntactic parse trees. We model the function tags assignment problem as a classification problem. Each function tag is regarded as a class and the task is to find what class\/tag a given node in a parse tree belongs to from a set of predefined classes\/tags. The paper offers the first systematic comparison of the two techniques, naive Bayes and decision trees, for the task of function tags assignment. The comparison is based on a standardized data set, the Penn Treebank, a collection of sentences annotated with syntactic information including function tags. We found out that decision trees generally outperform naive Bayes for the task of function tagging. Furthermore, this is the first large scale evaluation of decision trees based solutions to the task of functional tagging. <\/jats:p>","DOI":"10.1142\/s0218213008004011","type":"journal-article","created":{"date-parts":[[2008,6,24]],"date-time":"2008-06-24T09:38:40Z","timestamp":1214300320000},"page":"483-499","source":"Crossref","is-referenced-by-count":0,"title":["LARGE SCALE EXPERIMENTS WITH NAIVE BAYES AND DECISION TREES FOR FUNCTION TAGGING"],"prefix":"10.1142","volume":"17","author":[{"given":"MIHAI","family":"LINTEAN","sequence":"first","affiliation":[{"name":"Department of Computer Science, Institute for Intelligent Systems, The University of Memphis, Memphis, TN 38152, USA"}]},{"given":"VASILE","family":"RUS","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Institute for Intelligent Systems, The University of Memphis, Memphis, TN 38152, USA"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"rf1","first-page":"535","volume":"20","author":"Lappin S.","journal-title":"Computational Linguistics"},{"key":"rf5","volume-title":"Bracketing guidelines for treebank II style","author":"Bies A.","year":"1995"},{"key":"rf9","doi-asserted-by":"publisher","DOI":"10.1023\/A:1009778005914"},{"key":"rf13","doi-asserted-by":"publisher","DOI":"10.1109\/34.589207"},{"key":"rf14","volume-title":"Classification and Regression Trees","author":"Breiman L.","year":"1984"},{"key":"rf15","first-page":"81","volume":"1","author":"Quinlan J. R.","journal-title":"Machine Learning"},{"key":"rf16","volume-title":"C4.5: Programs for Machine Learning","author":"Quinlan J. R.","year":"1993"},{"key":"rf23","series-title":"International Computer Science Institute","volume-title":"FrameNet II: Extended Theory and Practice","author":"Ruppenhofer J.","year":"2006"},{"key":"rf24","doi-asserted-by":"publisher","DOI":"10.1162\/089120102760275983"},{"key":"rf26","volume-title":"Current Trends in Knowledge Acquisition","author":"Kononenko I.","year":"1990"},{"key":"rf27","volume-title":"Learning from Data: Artificial Intelligence and Statistics","author":"Pazzani M. J.","year":"1996"},{"key":"rf31","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"Witten I.","year":"2005"},{"key":"rf32","doi-asserted-by":"publisher","DOI":"10.1108\/eb046814"}],"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213008004011","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T17:10:00Z","timestamp":1565197800000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218213008004011"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,6]]},"references-count":13,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[2008,6]]}},"alternative-id":["10.1142\/S0218213008004011"],"URL":"https:\/\/doi.org\/10.1142\/s0218213008004011","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2008,6]]}}}