[PDF] Top 20 Learning a Lexical Simplifier Using Wikipedia

... n-gram language models capture how likely a par- ticular sequence is and can help identify candidate simplifications that are not appropriate in the con- text of the sentence. We included features from four different ... See full document

... Arabic Wikipedia, a semisupervised domain adap- tation setting for which we have no labeled training data in the target ...supervised learning on newswire text leads to poor target-domain ... See full document

... the Wikipedia collection is the parallel articles in ordinary English Wikipedia and Simple ...for learning simplification rules. Such learning can draw from machine translation, which learns ... See full document

... collocation learning and rationalize the choice of Wikipedia articles as the primary source from which to build a collocation ...words, using hedging and boosting devices, improving formality, and ... See full document

... We evaluated a neural network classifier compar- ing batch learning and curriculum learning. As a comparison ground, we also trained a linear clas- sifier, namely a Support Vector Machine (SVM) with a ... See full document

... However, the basic method has a problem. Consider if n(“earthquake”, “damages to hos- pitals”)=10 and n(“earthquake”) =100, while n(“damages”, “damages to hospitals”)=5 and n(“damages”)=5. We would prefer “damages” to be ... See full document

... Maureen Williams of Neumann University presented the session, ―One Shot? Make It Four! Planning and Assessing a Multi-Session Information Literacy Experiment,‖ in which she discussed expanding the traditional one-shot ... See full document

... activamente Wikipedia, en el marco de una asignatura de Estadística de un máster en ...de Wikipedia y materiales académicos de aprendizaje ...de Wikipedia, para cada concepto estadístico de la ... See full document

... lenging. Wikipedia contains over five million arti- cles in its English ...in Wikipedia is an impor- tant step towards more effective information ...Many Wikipedia articles have an infobox, a table ... See full document

... existing Wikipedia category that contains the tar- get entity, we extract and select a small set of query patterns by presuming that formulating search queries with these pat- terns optimizes the overall precision ... See full document

... When compiling, the compiler translates your source code into Microsoft Common Intermediate Language (MSIL), which is a CPU independent set of instructions that can be efficiently co[r] ... See full document

... problem of sentence compression, another English- to-English translation task. Knight and Marcu (2002) were one of the first to formalize text compression as a data-driven problem and pro- posed a probabilistic, ... See full document

... test set provided by Conneau et al. (2018), which selects the most frequent 200k words of each lan- guage as candidates for 1.5k query words. We translate a query word by retrieving its k near- est neighbours in the ... See full document

... The problem of information-extraction (IE), gen- erating relational data from natural-language text, has received increasing attention in recent years. A large, high-quality repository of extracted tu- ples can ... See full document

... of Wikipedia for various natural lan- guage processing ...proposed using the hierarchical cate- gory structure of Wikipedia to categorize text doc- ...of Wikipedia is the Wikify! system ... See full document

... machine learning, in developing techniques to perform intrin- sic qualitative evaluation of learned ...After learning topics from a collection of news articles and a collection of books, we ask humans to ... See full document

... inadvertently learning “hints” from the topics in the texts that would not exist in another experi- ment addressing the same ...find lexical pair features such as (?, yes) and (why, because) to be highly ... See full document

... data using a set of 152 manually labeled blogs to train their ...chine learning (i.e., using a rule-based ...it using its online search results and/or Wikipedia ...machine ... See full document

... for Wikipedia. After learning a transformation of one vec- tor space to the other, and adjusting simi- larity values according to term frequency, we identify words whose usage differs greatly between the ... See full document

... However, these knowledge resources still lack semantic information about language units such as phrases and collocations. For instance, which semantic classes are expected as a direct object of the verb break? What kinds ... See full document