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 Improving Diversity in Ranking using Absorbing Random Walks
diversity-based reranking for reordering documents and pro-ducing summaries. In SIGIR’98. P.G. Doyle and J.L. Snell. 1984. Random Walks and Electric Networks. Mathematical Assoc. of America. Gunes¸ Erkan and Dragomir R. Radev. 2004. LexRank: Graph-¨ based centrality as salience in text summarization. Journal of Artificial Intelligence ......
Extractive Summarization using Deep Learning
Text Summarization can be classi ed into extractive summarization and ab-stractive summarization based on the summary generated. Extractive summa-rization is creating a summary based on strictly what you get in the original text. Abstractive summarization mimics the process of paraphrasing a text. Text(s)...
Google AI Blog: Text summarization with TensorFlow
Extractive and Abstractive summarization One approach to summarization is to extract parts of the document that are deemed interesting by some metric (for example, inverse-document frequency) and join them to form a summary. Algorithms of this flavor are called extractive summarization. Original Text: Alice and Bob took the train to visit the zoo.
SUMMARIZATION: (1) USING MMR FOR DIVERSITY-BASED RERANKING ...
appropriate passages for text summarization. Preliminary results indicate some benefits for MMR diversity ranking in ad-hoc query and in single document summarization. The latter are borne out by the trial-run (unofficial) TREC-style evaluation of summarization systems. However, the clearest advantage is
Sparse Dictionary-based Attributes for Action Recognition ...
Sparse Dictionary-based Attributes for Action Recognition and Summarization. 08/01/2013 ∙ by Qiang Qiu, et al. ∙ University of Maryland ∙ 0 ∙ share . We present an approach for dictionary learning of action attributes via information maximization.
Diversity-Promoting GAN: A Cross-Entropy Based Generative ...
Diversity-Promoting GAN: A Cross-Entropy Based Generative ... Xu et al.,2018a), text summarization (Ma et al.,2018a), and table summarization (Liu et al., 2017). In these tasks, most of the systems are ... that the cross-entropy based reward for novel text is high and does not saturate, while the reward for...
Multi-document summarization - Wikipedia
The multi-document summarization technology is now coming of age - a view supported by a choice of advanced web-based systems that are currently available. Ultimate Research Assistant [2] - performs text mining on Internet search results to help summarize and organize them and make it easier for the user to perform online research.
LDA for Text Summarization and Topic Detection - DZone AI
Text Summarization A classic use case in text analytics is text summarization; that is the art of extracting the most meaningful words from a text document to represent it.
Diversity in Organizations | Boundless Management
Diversity: The state of being different; achieving variability. ... As a result of this criticism, the equal-opportunity movement evolved towards a model based more on social justice. This perspective still promotes the active seeking out of diversity in the workplace, but does so primarily based on the intrinsic value of employees with ...
Semi-Automatic Indexing of Full Text Biomedical Articles
We started back with the best MMI only model: title & abstract, captions, introduction, results, discussion, other, no header. As with the title and abstract based REL indexing, the best performance is achieved when we use all 10 of the available citations for each section. Table 2 shows this result in the context of the other major model versions.
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