We present methods of extractive query-oriented single-document summarization using a
deep auto-encoder (AE) to compute a feature space from the term-frequency (tf) input. Our …

Traditional Arabic text summarization (ATS) systems are based on bag-of-words
representation, which involve a sparse and high-dimensional input data. Thus …

We propose an image-text alignment framework to match images with text, and take blog
article summarization as the main application. Objects in an image are first detected, from …

In a fast-changing media ecosystem, professionals and enterprises in the News and Media
industry face new challenges that they should address to maximize their productivity and …

This paper presents an image recommendation system called “News2Image”, which takes
as input a news text and outputs a small set of images selected from the database such that …

Algorithms are increasingly playing an important role in the production of news content with
growing computational capacity. Moreover, the use of the algorithm is taking up traditional …

In these days, personalized news recommender systems (RSs) have become an important
and promising research field in the World Wide Web. RSs provide fast access to real-time …

Automated news generation systems have been generating text-based news articles ever
since the advancement of Natural Language Processing and machine-learning algorithms …

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