Πληροφορίες μαθήματος

This course is concerned with extracting useful information from unstructured big data, mostly data in the form of text and speech. The course will introduce core concepts, models, and algorithms from machine learning, natural language processing, and speech processing that can be used to recognize speech, and normalize, classify, cluster, tag, parse, disambiguate, and extract information from texts and spoken utterances. Several application areas will be considered, including filtering e-mails and social media messages, summarizing opinions and performing sentiment analysis (e.g., for particular products) in social media or discussion fora, monitoring spoken dialogues in call centers (e.g., to check for compliance with protocols), populating databases with information extracted from news feeds (e.g., company mergers and acquisitions), finding answers to scientific questions in the research literature. The students will have the opportunity to learn how to use existing tools (e.g., machine learning, speech recognition, and natural language processing toolkits) by applying them to realistic datasets. Key concepts and applications of multimodal content analytics will also be covered if time permits.