[PDF] Top 20 Mining for Domain specific Parallel Text from Wikipedia

... Since our extraction system is merely a proto- type, there are several ways to improve its per- formance, including better filtering for in-domain articles, finer grained alignment and more so- phisticated ... See full document

... in text mining, such as text clustering, text classification, information extraction, and sentiment analysis; unlike standard textual data which has several sentences and hence, a surrounding ... See full document

... benefit from Wikipedia’s broad and contemporary ...to domain terms, and phrases from relevant do ents as illustrated in Figure ...by mining Wikipedia’s ...which Wikipedia has ... See full document

... face text-based matching between formulas and text, as well as patterns representing relationships between them showed promise for mining math- ematical knowledge from ...by mining ... See full document

... To obtain transliteration similarity measures, we apply the Forward algorithm of the trained pair HMM from section 3.1 to all the remaining Wikipedia topics. For each word in an English topic, the algorithm ... See full document

... for mining transliterations from Wikipedia finds its origins as an alternative DBN representation of a memoryless stochastic trans- ducer using the general probabilistic graphical modeling (PGM) ... See full document

... Neelakantan and Collins (2015) applied Ca- nonical Correlation Analysis to calculate repre- sentation of phrases which were then used for syn- onym classification. McCrae and Collier (2008) used automatically generated ... See full document

... information from text and associate it to other concepts and ...expressions from various document types (UzZaman and Allen, 2010; Llorens et ... See full document

... used Wikipedia based knowledge bases is DBpedia and its semantic annotation system DBpedia Spotlight (Mendes et ...annotate text with URIs from ...derived from Wikipedia in order to ... See full document

... that domain-specific classification yields better analysis and better understanding for the ...use domain specific language to classify the emotional content. Domain specificity is ... See full document

... This paper presents a new methodology that helps in illustrating different future scenarios that can occur as a chain reaction to the current social or political situations as depicted by analyzing newspapers as an ... See full document

... searching using metadata content requires that ei- ther the metadata be translated into a language with which the user is able to search or that the search query be translated into the language of the meta- data. This ... See full document

... After defining a threshold for each measure, the sentence pairs with a similarity higher than the threshold are ex- tracted as parallel sentences. Authors report a lot of ex- periments and conclude that averaging ... See full document

... open domain data such as Wikipedia, us- ing common Chinese characters for filtering is more effec- tive than a domain specific ...erroneous parallel sentence ...lected from the ... See full document

... Available Online at www.ijpret.com 1203 and IOC in feature reduction also provide comparably good or better extracted features for classification [1].The effectiveness of PTM (IPE) to find the correlation between ... See full document

... different from prior work on ...on text of any ...of Wikipedia which is highly ...in Wikipedia. Furthermore, we compute concept relatedness on a domain-specific hierarchy that ... See full document

... pages from specific ...the text extracted from the web pages is formal and suitable for auto process by the ...the text is extracted from these candidate pairs omitting html ... See full document

... having domain- specific corpora by creating a domain-specific sentiment lexicon from the raw corpora built as described in Section ...A domain-specific sentiment lexicon ... See full document

... tion, and a few additional roles, such as star, team- mate, etc.). We handle this by limiting the number of classes considered to 3 per entity. This constraint re- duces the total number of distinct classes to 26, 165, ... See full document

... rules from natural-language corpora, and these rules are used to predict additional information to extract from future documents, thereby improving the recall of ...for mining rules from ... See full document