[PDF] Top 20 Cross Lingual Latent Topic Extraction

... in cross-lingual corpus, we use some event names, ...about topic ’Championship’ combined with the other two topics in the same ...’Championship’ topic may not be easy to extract, because the ... See full document

... years, topic models were applied to more and more multilingual tasks (Wang et ...proved cross-lingual topical relevance model based on the latent topics of top ranked ...a ... See full document

... Cross-lingual topic modelling has applications in machine translation, word sense disam- biguation and terminology ...Multi- lingual extensions of approaches based on la- tent (LSI), ... See full document

... regarding topic modeling of information flow in multilingual news ...situation, topic models such as LDA (Latent Dirichlet Allocation) and DTM (dynamic topic model) are quite effective in ... See full document

... on latent-cross lingual topics estimated from the data of higher quality ...the latent cross-lingual topics estimated from training data, and the quality of these latent ... See full document

... novel cross-lingual struc- ture transfer learning framework to project source language (SL) training data and target language (TL) test data into the common semantic space, so that we can train a relation ... See full document

... exploits Latent Semantic Analysis (LSA) to extract domain terminology from a large open domain corpus, as an answer to a user ...the extraction of domain ontologies from WordNet on the fly without the need ... See full document

... The cross-language information is expected to reinforce language similarities and value language dissimilarities, and better understand articles in terms of ...these topic-related scores during training by ... See full document

... Compared to traditional entity linking, the unique challenge of linking to GeoNames is that it is very scarce, without rich linked structures or text descriptions. Only 500k out of 4.7 mil- lion entities in Wikipedia are ... See full document

... a cross-lingual Word Sense Disambiguation ( WSD ) method which exploits the output of data-driven Word Sense Induction ( WSI ) (Apidianaki, 2009), and demonstrate how feature disambiguation en- hances the ... See full document

... Step 2: Run text clustering algorithm (e.g., K-means) on collections with either language to find mono-lingual text clusters. Then as to have enough clusters in two languages to align, we select 500 clusters for ... See full document

... feature extraction pipeline based on a variety of standard natural language pro- cessing (NLP) tools and a machine learning com- ponent to predict coreference links including both pronominal anaphora and noun-noun ... See full document

... automatic cross-lingual similarization of dependency grammars, and learnt grammars with higher cross-lingual similarity while maintaining the non-triviality of the ... See full document

... which large bitexts with a ‘bridge’ language B exist, readily yielding reasonably-good alignment models for S-B and B -T . We are however specifically in- terested in the S-T pair, for which we only possess a small ... See full document

... inter- lingual representation, and language-specific ...mono- lingual corpora show that multilingual unsu- pervised model performs better than the sepa- rately trained bilingual models achieving im- ... See full document

... perhaps cross-language in- formation retrieval, which is concerned with matching queries posed in one language to docu- ment collections in a second ...for cross- language information retrieval have been ... See full document

... are cross- lingually more stable than function words (Croft et ...to cross-lingual transfer, it also supports monolingual applications with a quality comparable to language- specific annotations ... See full document

... space, Latent semantic analysis, Probabilistic latent semantic model and Latent Dirichlet allocation can be used to derive word meaning representation based on the analysis of statistics ...various ... See full document

... information extraction (IE) is a weakly supervised IE paradigm that aims to extract relation-independent informa- tion from large-scale natural language documents without significant annotation ...the ... See full document

... Relation extraction (RE) is the task of assigning a semantic relationship between a pair of arguments. The two major types of RE are closed domain and open domain RE. While closed-domain RE systems (Bunescu and ... See full document