learning bigrams from unigrams

Ngày tải lên: 23/03/2014, 17:20

... * You are twelve years We can say: You are twelve or You are twelve years old snake Learning from mistakes English Questions • What • How • Why • Who • How much… • How many… • How long • Where • When • … • is • are • do • does • can • Did • … Subject verb …...

Ngày tải lên: 15/09/2013, 03:10

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Ngày tải lên: 17/03/2014, 06:20

Ngày tải lên: 23/03/2014, 03:20

Ngày tải lên: 24/03/2014, 03:20

Ngày tải lên: 08/05/2014, 17:04

Ngày tải lên: 17/08/2013, 10:57

... help their staff to write project Learning from the project 201 proposals and to prepare the documentation that is needed throughout the project. SHARING LEARNING FROM A PROJECT One of the questions ... from their normal roles at work. Projects can often provide a training ground for teamworking and leadership. Different types of learning for individuals and for organizations can be gained from ... project. For this learning to be useful it needs to be recognized and captured so that it can inform future development. ORGANIZATIONAL LEARNING ABOUT MANAGEMENT OF PROJECTS Organizational learning is...

Ngày tải lên: 24/10/2013, 08:20

... of Korea, 8-14 July 2012. c 2012 Association for Computational Linguistics Learning the Latent Semantics of a Concept from its Definition Weiwei Guo Department of Computer Science, Columbia University, New ... Science, Columbia University, New York, NY, USA weiwei@cs.columbia.edu Mona Diab Center for Computational Learning Systems, Columbia University, New York, NY, USA mdiab@ccls.columbia.edu Abstract In this ... discover more overlapping words. How- ever, exact word matching is lossy. Below are two definitions from WN: bank#n#1: a financial institution that accepts deposits and channels the money into lending...

Ngày tải lên: 19/02/2014, 19:20

... non-comparative sen- tences from comparative sentence candidates with a CKL2 keyword, we employ machine learning techniques (MEM and Naïve Bayes). For feature extraction from each comparative- sentence ... comparative sentences from text documents. This paper first investigates many comparative sentences referring to pre- vious studies and then defines a set of compar- ative keywords from them. A sentence ... called a comparative-sentence candidate. Finally, we use machine learning techniques to eliminate non-comparative sentences from the candidates. As a result, we achieved signifi- cant performance,...

Ngày tải lên: 20/02/2014, 09:20

... performance is very encouraging, especially as the learning is from such limited training data. Feature Evaluation. The best performing learning algorithm, SVM, was then used to ex- amine ... agreement”. Human agreement (the upper bound) for this learning task increases from 44.4% to 79.8%. 10-fold cross validation was also used to train the learning models, which were then tested on the ... later evaluation of machine learning experiments. For example, for a given event with a known gold standard duration range from 1 hour to 4 hours, if a ma- chine learning program outputs a duration...

Ngày tải lên: 20/02/2014, 12:20

... describes a method for automat- ically learning effective dialogue strategies, generated from a library of dialogue content, using reinforcement learning from user feed- back. This library includes ... your exercise). 5 Dialogue Policy Optimization with Reinforcement Learning Reinforcement learning refers to a class of machine learning algorithms in which an agent explores an environment and ... have focussed their attention on the learning aspect of the task, examining, for example hybrid reinforce- ment/supervised learning (Henderson et al., 2005). Previous work on learning dialogue management strategies...

Ngày tải lên: 20/02/2014, 12:20

... Cardie (2002b) for details. Learning algorithms. We consider three learning algorithms, namely, the C4.5 decision tree induction system (Quinlan, 1993), the RIPPER rule learning algorithm (Cohen, ... select these learning- based coreference systems and acquire the ranking model. 3.1 Selecting Coreference Systems A learning- based coreference system can be defined by four elements: the learning algorithm ... the correct partition derived from the training text. We then assign rank to the -th lowest scored parti- tion. 4 Effectively, the learning algorithm learns what a good partition is from the scoring program. 4 Two...

Ngày tải lên: 20/02/2014, 15:20

... Quinlan. 1986. Induction of decision trees. In Machine Learning I (I), pages 81-106. R. L. Rivest. 1987. Learning Decision Lists. In Machine Learning 2, pages 229-246. R. F. Simmons and Yeong-Ho ... are unjustifiably remote from the current focus of a parse state. The feature collection is basically independent from the supervised parse action acquisition. Before learning a decision structure ... Dependencies. In 3~th Proceed- ings of the ACL, pages 184-191. U. Hermjakob. 1997. Learning Parse and Trans- lation Decisions From Examples With Rich Con- text. Ph.D. thesis, University of Texas at Austin,...

Ngày tải lên: 22/02/2014, 03:20

... same NER tag, ignor- ing unigrams (since unigrams are already included in the base model). Using the Verb Path example above, the bigram feature Hu Jintao is included. 4 Learning Time Constraints This ... dependency path from the nearest verb to the year expression. The following snippet will include the feature, ‘ex- pected prep in pobj 2002’. 1 http://nlp.stanford.edu/software Finance Article from Jan. ... documents from each year. The test set in- cludes 11,300 documents in each year (months June and August) for a total of 113,000 test doc- uments. The development set includes 7,300 from July...

Ngày tải lên: 07/03/2014, 18:20

... 184–188, Uppsala, Sweden, 11-16 July 2010. c 2010 Association for Computational Linguistics Learning Common Grammar from Multilingual Corpus Tomoharu Iwata Daichi Mochihashi NTT Communication Science ... languages from non-parallel multilingual corpora in an unsupervised fashion. For this purpose, we assume a generative model for multilingual corpora, where each sentence is generated from a language ... borrowing from nearby languages, and 3) the innate abilities of humans (Chomsky, 1965). We assume hidden commonalities in syntax across languages, and try to extract a common grammar from non-parallel...

Ngày tải lên: 07/03/2014, 22:20

... 2011. c 2011 Association for Computational Linguistics Learning Condensed Feature Representations from Large Unsupervised Data Sets for Supervised Learning Jun Suzuki, Hideki Isozaki, and Masaaki Nagata NTT ... addition to F in supervised learning, i.e., F ∪ C. In contrast, in our method H is directly induced from F with the help of an existing model already trained by supervised learning with F, and used ... 319–326. John Duchi and Yoram Singer. 2009. Efficient On- line and Batch Learning Using Forward Backward Splitting. Journal of Machine Learning Research, 10:2899–2934. Terry Koo and Michael Collins. 2010....

Ngày tải lên: 07/03/2014, 22:20

... null label is NO-REL. train/test split from Table 1 and the feature sets: Syntactic The syntactic features from Section 4. Semantic The semantic features from Section 4. All Both syntactic and ... 177–180, Columbus, Ohio, USA, June 2008. c 2008 Association for Computational Linguistics Learning Semantic Links from a Corpus of Parallel Temporal and Causal Relations Steven Bethard Institute for ... 81.2% on temporal relations and 77.8% on causal re- lations. We trained machine learning mod- els using features derived from WordNet and the Google N-gram corpus, and they out- performed a variety...

Ngày tải lên: 08/03/2014, 01:20