While automatic keyphrase extraction has been examined extensively, state-of-theart
performance on this task is still much lower than that on many core natural language …

Sentiment analysis is a solution that enables the extraction of a summarized opinion or
minute sentimental details regarding any topic or context from a voluminous source of data …

Short texts are popular on today's web, especially with the emergence of social media.
Inferring topics from large scale short texts becomes a critical but challenging task for many …

We propose an unsupervised keyphrase extraction model that encodes topical information
within a multipartite graph structure. Our model represents keyphrase candidates and topics …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

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 …

Keyphrases can provide highly condensed and valuable information that allows users to
quickly acquire the main ideas. The task of automatically extracting them have received …

In recent years, online social networking has revolutionized interpersonal communication.
The newer research on language analysis in social media has been increasingly focusing …

Detecting events in real-time from the Twitter data stream has gained substantial attention in
recent years from researchers around the world. Different event detection approaches have …

The proliferation of social networking services has resulted in a rapid growth of their user
base, spanning across the world. The collective information generated from these online …