We designed experiments involving spatial color image databases modeling and summarization, and text classification to show the robustness, flexibility and merits of our approach.
Document search, clustering, classification, summarization, trend detection, and monitoring are examples of tasks.
The purpose of this database is manifold; it can be used for training and evaluation of event detection and summarization algorithms, for classification and recognition of audio-visual and cross-media events, as well as for emotion tracking.
In addition, our work does not focus on event detection, classification or summarization, as most of the prior work on event analysis does.
According to Money and Agius [6], there is another interesting classification for video summarization techniques: 1) internal summarization techniques that analyse information sourced directly from the video stream, and 2) external ones that analyse information not sourced directly from the video stream.
Part II: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization; information retrieval and text classification; practical applications.
Keyphrase extraction also provides useful resources for text clustering [8], text classification [35], and document summarization [32].
The use of distributed word representations (word embeddings) can be seen in several works of this area in tasks such as classification [88, 152, 153], summarization [154], and information retrieval [155].
The proposed framework is designed to cope with the following tasks: trendy topics detection, opinion classification, credibility assessment, and numeric summarization.
LSA has been greatly successful in many information retrieval applications such as document classification [ 40], spam filtering [ 41], and text summarization [ 42].
