Báo cáo khoa học: "Learning Semantic Links from a Corpus of Parallel Temporal and Causal Relations" doc

... Section 4. Semantic The semantic features from Section 4. All Both syntactic and semantic features. All+Tmp (Causals Only) Syntactic and semantic features, plus the gold-standard temporal label. We ... existing corpora are missing some crucial pieces for study- ing temporal- causal interactions. Our research aims to fill these gaps by building a corpus of parallel t...

Ngày tải lên: 08/03/2014, 01:20

... Institute of Science and Technology (NAIST) 8916-5 Takayama, Ikoma, Nara 630-0192, Japan mamoru-k@is.naist.jp Shimpei Makimoto and Kei Uchiumi and Manabu Sassano Yahoo Japan Corporation Midtown ... facilitates the computation time and reduces the size of instance-pattern matrix drastically. When a query was a variant of a term or con- tains spelling mistakes, we estimated...

Ngày tải lên: 08/03/2014, 01:20

... Corpus Tomoharu Iwata Daichi Mochihashi NTT Communication Science Laboratories 2-4 Hikaridai, Seika-cho, Soraku-gun, Kyoto, Japan {iwata,daichi,sawada}@cslab.kecl.ntt.co.jp Hiroshi Sawada Abstract We ... 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

... dictionary and n-gram based content analysis and achieved 91.5% accuracy using an SVM classifier. We also use a super- vised machine learning approach, but classifica- tion by gender is naturally a binary ... Social media and young adults. Ian Mackinnon. 2006. Age and geographic inferences of the livejournal social network. In In Statistical Network Analysis Workshop. Andrew Y Ng...

Ngày tải lên: 07/03/2014, 22:20

... inter-annotator agreement when the judgments are intervals on a scale; and we have shown that machine learning techniques applied to the annotated data considerably out- perform a baseline and approach ... data; some can han- dle more general data, such as data in interval scales or ratio scales. However, none of the tech- niques directly apply to our data, which are ranges of...

Ngày tải lên: 20/02/2014, 12:20

... Proceedings of the Ninth Confer- ence on Computational Natural Language Learning (CONLL-05), Ann Arbor, Michigan. Joao Graca, Kuzman Ganchev, and Ben Taskar. 2008. Expectation maximization and posterior ... modification of the beam search algo- rithm, where we keep a set of candidate meanings (partial semantic representations) and compute an alignment for each of them using...

Ngày tải lên: 07/03/2014, 22:20

... labeled data. While labeled data are difficult to obtain, unlabeled data are readily available and plentiful. Therefore, this paper advocates using a bootstrapping framework and a feature projection ... robustness from noisy data (Ko and Seo, 2004). How can labeled training data be automatically created from unlabeled data and title words? Maybe unlabeled data don’t ha...

Ngày tải lên: 20/02/2014, 16:20

... Computational Natural Language Learn- ing: Shared Task, pages 28–34. Malvina Nissim, Shipra Dingare, Jean Carletta, and Mark Steedman. 2004. An annotation scheme for information status in dialogue. ... reso- lution and IS determination can benefit from each other, it may be possible to formulate an approach where the two tasks can mutually bootstrap. We investigate rule-based and learn...

Ngày tải lên: 22/02/2014, 03:20

... which uses Ratnaparkhi (1996)’s feature set and conducts a beam (=5) search in the unconstrained space, achieves a tagging accuracy of 97.16%. Tagging accuracy is measured by the percentage of correct predictions ... Word segmentation as character tagging Considering the ambiguity problem that a Chinese character may appear in any relative position in a word and the out -of- v...

Ngày tải lên: 07/03/2014, 18:20

... understanding and lasting motiva- tion, which is useful for educational sys- tems. In our approach, we train a ranker that learns from data the appropriate ranking of definitions based on features ... important for quiz-style ranking, we learn the appropriate ranking of definitions from data. The approach is the same as that of (Xu et al., 2005) in that we adopt a machine learni...

Ngày tải lên: 08/03/2014, 03:20