Part 1. Context Computing. Context is used as a term for packaging information for a particular need. A criterion for selecting or prioritization information from a broader pool of information could be called contextual model. Search can be contextual: The relevance of Context in computing seems to be growing. Many application areas see an opportunity in extending its value by introducing "context sensitivity". More details do to be found in ISWC2006 Tutorial on "context sensitivity": Part 2. Text Mining & Light Weight Semantics. Videolectures discusses the following topics: - levels of text representations - modeling the data (Support Vector Machine) - classification into large taxonomies (DMoz) - visual & contextual search (Search Point) - multilingual search - news bias, news visualization - text enrichment (Enrycher) - knowledge based summarization - question answering (AnswerArt) - Cyc knowledge base and reasoning