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[PDF] Top 20 Measuring the Similarity between Automatically Generated Topics

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Measuring the Similarity between Automatically Generated Topics

Measuring the Similarity between Automatically Generated Topics

... the topics’ word probability distributions (Section ...high similarity to top- ics that contain ambiguous words, resulting in low correlations with human ... See full document

6

Measuring the Similarity between TV Programs using Semantic Relations

Measuring the Similarity between TV Programs using Semantic Relations

... the similarity between TV program summaries in Electronic Program Guides (EPGs) in ...for measuring the similarity between programs can exclude exactly similar content and select only ... See full document

16

A Statistical Model for Measuring Structural Similarity between Webpages

A Statistical Model for Measuring Structural Similarity between Webpages

... structural similarity between HTML files was first introduced in (Resnik, 1998), where a linearized HTML structure of candidate pairs was used to confirm parallelism of ...tag similarity and a ... See full document

8

Measuring Distributional Similarity in Context

Measuring Distributional Similarity in Context

... meaning similarity as operationalized by vector-based models has found widespread use in many tasks ranging from the acquisition of synonyms and para- phrases to word sense disambiguation and tex- tual ...for ... See full document

11

A Probabilistic Model for Measuring Grammaticality and Similarity of Automatically Generated Paraphrases of Predicate Phrases

A Probabilistic Model for Measuring Grammaticality and Similarity of Automatically Generated Paraphrases of Predicate Phrases

... The most critical issue in generating and recognizing paraphrases is development of wide-coverage paraphrase knowledge. Previous work on paraphrase acquisition has collected lexicalized pairs of expres- sions; however, ... See full document

8

Semantic Relatedness from Automatically Generated Semantic Networks

Semantic Relatedness from Automatically Generated Semantic Networks

... to measuring semantic relatedness, we first automatically build a large semantic network from text and then measure the similarity of two terms by the similarity of the local networks around ... See full document

5

Explore with caution: mapping the evolution of scientific interest in physics

Explore with caution: mapping the evolution of scientific interest in physics

... period between 1980 and ...tween topics in the careers of ...exploitation measuring the similarity, in terms of topics, between the production during the first and last year of ... See full document

15

Distributional Semantics Beyond Words: Supervised Learning of Analogy and Paraphrase

Distributional Semantics Beyond Words: Supervised Learning of Analogy and Paraphrase

... the similarity of word pairs, phrases, and sentences (briefly, tuples; ordered sets of words, contiguous or ...similarities between the com- ponent words in the ...tional similarity (analogy) and ... See full document

14

Re Ranking Words to Improve Interpretability of Automatically Generated Topics

Re Ranking Words to Improve Interpretability of Automatically Generated Topics

... generate topics and the number of topics for each dataset was set based on optimising for coherence which yielded 35 for NYT, 45 for MEDLINE and 35 for ...The automatically generated topic ... See full document

12

Evaluation of automatically generated English vocabulary questions

Evaluation of automatically generated English vocabulary questions

... of generated questions; otherwise, those questions cannot be used for its intended ...(2015) generated questions related to particular topics and evaluated the syntactic correctness of the ... See full document

21

How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations

How to Combine Text-Mining Methods to Validate Induced Verb-Object Relations

... MB), used as a test corpus, and called corpus T . The second one, called corpus V , comes from the French newspaper Le Monde, and plays the role of the validation corpus. It con- tains more than 60,000 news items (123 ... See full document

24

ArabTAG: from a Handcrafted to a Semi automatically Generated TAG

ArabTAG: from a Handcrafted to a Semi automatically Generated TAG

... Arabic TreeBank – PATB). The corpus they used is the Part 1 v 2.0 of PATB (Maamouri et al., 2003; Maamouri and Bies, 2004). This extraction in- volved a reinterpretation of the corpus in depen- dency structures. The ... See full document

9

Mining Newsorthy Topics from Social Media

Mining Newsorthy Topics from Social Media

... the similarity between two terms as the fraction of messages in the same time slot that contain both of them, so it is highly likely that the term clusters whose similarities are high represent the same ... See full document

13

A Proposed Framework for a Distributed CBIR System based on Salient Regions and RF Techniques

A Proposed Framework for a Distributed CBIR System based on Salient Regions and RF Techniques

... varied between the Annotation Based Image Retrieval (ABIR) or the meta-data approach which is a traditional method for image retrieval that makes use of the meta data of image such as the textual descriptions, ... See full document

5

Automatically generated NE tagged corpora for English and Hungarian

Automatically generated NE tagged corpora for English and Hungarian

... to automatically prepare sentences where NEs are accurately tagged, two tasks need to be per- formed: identifying entities in the sentence and tag- ging them with the correct ... See full document

9

Automatically learning topics and difficulty levels of problems in online judge systems

Automatically learning topics and difficulty levels of problems in online judge systems

... to automatically mine topic and difficulty information from users’ learning traces on OJ ...their topics or identify questions from multiple volumes but all about the same topic for ... See full document

35

Automatically Extracting Polarity Bearing Topics for Cross Domain Sentiment Classification

Automatically Extracting Polarity Bearing Topics for Cross Domain Sentiment Classification

... of topics varying between 1 and 200, corresponding to feature clusters varying between 3 and ...polarity topics from JST reveals that when the topic number is small, each topic cluster ... See full document

9

Evaluation of Automatically Generated Pronoun Reference Questions

Evaluation of Automatically Generated Pronoun Reference Questions

... and between MGQs and HMQs is important because we cal- culate the student-wise score correlation between scores from MGQs and HMQs as explained later in ... See full document

10

Query By Image Content System Based On Colour And Texture Feature Of Image

Query By Image Content System Based On Colour And Texture Feature Of Image

... Rule enforcement agencies have maintained large database of visual evidence like past suspects facial photographs, fingerprints and shoeprints. By the use of this system, they can compare evidence from the scene of the ... See full document

5

Best practices for the human evaluation of automatically generated text

Best practices for the human evaluation of automatically generated text

... evaluation are usually treated as subjective (as in the case of judgments of fluency, adequacy and the like). It is also conceivable that these cri- teria can be assessed using more objective mea- sures, similar to ... See full document

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