Within the past five years, micro-blogs have greatly developed and now become one indispensable information source. In this talk, I will introduce the task of information extraction for micro-blogs. One main common research challenge is the dearth of information in a single micro-blog, rooted in the short and noisy nature of micro-blogs. To attack this challenge, I will present several collective inference algorithms, which are applied to NER, SRL and EE, respectively, yielding remarkable improvements over the baselines. In the end, I will present a semantic search of micro-blogs called QuickView, which integrates various information extraction technologies and enables categorized browsing and advanced search of micro-blogs.