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We propose a framework for assisting human editors to manage this information disparity, using tools from machine translation and machine learning. Given source and target documents in two different languages, our system automatically identifies information nuggets that are new with respect to the target and suggests positions to place their translations. We perform both real-world experiments and large-scale simulations on Wikipedia documents and conclude our system is effective in a variety of scenarios.<\/jats:p>","DOI":"10.1145\/2442076.2442077","type":"journal-article","created":{"date-parts":[[2013,3,25]],"date-time":"2013-03-25T13:31:59Z","timestamp":1364218319000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["Managing information disparity in multilingual document collections"],"prefix":"10.1145","volume":"10","author":[{"given":"Kevin","family":"Duh","sequence":"first","affiliation":[{"name":"NTT Communication Science Laboratories, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ching-Man Au","family":"Yeung","sequence":"additional","affiliation":[{"name":"NTT Communication Science Laboratories, Huawei, Hong Kong"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tomoharu","family":"Iwata","sequence":"additional","affiliation":[{"name":"NTT Communication Science Laboratories, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masaaki","family":"Nagata","sequence":"additional","affiliation":[{"name":"NTT Communication Science Laboratories, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2013,3,22]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics. 62--69","author":"Adafre F. 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