[PDF] Top 20 Better Summarization Evaluation with Word Embeddings for ROUGE
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Better Summarization Evaluation with Word Embeddings for ROUGE
... The pyramid method originally proposed by Passonneau et al. (2005) is another staple in DUC/TAC. However it is a semi-automated method, where significant human intervention is required to identify units of information, ... See full document
6
Centroid based Text Summarization through Compositionality of Word Embeddings
... MSS task, we performed the tuning of parameters using only the training set. To find the best topic and similarity threshold parameters we run a grid search as explained in Section 4.1. The grid search is performed for ... See full document
10
A study of semantic augmentation of word embeddings for extractive summarization
... an Rouge-1 and Rouge-2 score of ...trained embeddings performs at 0.196 and 0.015 for Rouge-1 and Rouge-2, respectively, and ... See full document
10
Evaluation of Croatian Word Embeddings
... reveal better performance than tests ori- ented to semantic, but they still have significantly worse performance rather than on ...slightly better score is given in categories with word pairs in the ... See full document
7
An evaluation of Czech word embeddings
... sub- word information into embeddings (which is, among other, motivated by morphologically rich languages), models trained on lemmata perform better that their counterparts trained on ... See full document
11
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?
... in word-level word ...a word in a given ...intrinsic evaluation methods also depends on whether the relations in the test word pairs match the distribution of senses of these words in a ... See full document
7
Attentive Mimicking: Better Word Embeddings by Attending to Informative Contexts
... novel evaluation method that explicitly evaluates embeddings for rare and medium-frequency words by downsampling fre- quent words from the WWC to a fixed number of ...skipgram embeddings obtained ... See full document
6
Evaluation methods for unsupervised word embeddings
... predict word frequency categories based on word ...All word embeddings do better than random, suggesting that they contain some frequency in- ...other embeddings, accuracy for ... See full document
10
Geographical Evaluation of Word Embeddings
... random embeddings, each value is selected randomly from uniform distribution be- tween −1 and ...random embeddings are then evaluated in the same way as normal ...random embeddings. The comparison of ... See full document
9
SWOW 8500: Word Association task for Intrinsic Evaluation of Word Embeddings
... Downstream evaluation of pretrained word embeddings is expensive, more so for tasks where current state of the art models are very large ...Intrinsic evaluation us- ing word similarity ... See full document
9
Re evaluating Automatic Summarization with BLEU and 192 Shades of ROUGE
... score better quality system-generated summaries higher than worse quality system-generated summaries, how- ...to evaluation of MT met- rics by correlation with human judgment, where metrics only receive ... See full document
10
Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation
... contextualized word embeddings into both the part of speech tagger and dependency parser; 2) ensem- bling parsers trained with different initial- ...final evaluation, our system was ranked first ... See full document
10
Relational Word Embeddings
... specific evaluation on ...which word vectors capture semantic properties which has shown to strongly correlate with performance in downstream tasks such as text categorization and sentiment analy- ...of ... See full document
11
Uncovering Divergent Linguistic Information in Word Embeddings with Lessons for Intrinsic and Extrinsic Evaluation
... tailor word embeddings in the semantics/syntax and similarity/relatedness axes without the need of additional ...in word analogy and word similarity, we show that standard embed- ding models ... See full document
10
Extractive Summarization using Continuous Vector Space Models
... Automatic summarization can help users extract the most important pieces of infor- mation from the vast amount of text digi- tized into electronic form ...automatic summarization is the no- tion of ... See full document
9
Affinity Preserving Random Walk for Multi Document Summarization
... ment cluster. The sentences with little informa- tion about the document cluster should not be in- cluded in the summary. The second one is di- versity. The information overlap between sum- mary sentences should be as ... See full document
11
Hypothesis Testing based Intrinsic Evaluation of Word Embeddings
... We introduce the cross-match test - an exact, distribution free, high-dimensional hypothesis test as an intrinsic evaluation metric for word embeddings. We show that cross-match is an effective means ... See full document
5
Medical Word Embeddings for Spanish: Development and Evaluation
... sentence embeddings for clinical and biomedi- cal texts, called BioSentVec trained on PubMed and clinical notes from the MIMIC-III Clini- cal Database(Johnson et ...train word embeddings for English ... See full document
10
Embeddings for Word Sense Disambiguation: An Evaluation Study
... As was analyzed by Lee and Ng (2002), conven- tional WSD systems usually make use of a fixed set of features to model the context of a word. The first feature is based on the words in the surround- ings of the ... See full document
11
Morphological Word Embeddings
... next word, encouraging the resulting embeddings to encode ...produces word- embeddings that better preserve morphological rela- ... See full document
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