Project Ibis is a CMIC effort to measure, analyze and enhance Web Search in Arabic. It involves collecting and mining search log information and user feedback, prototyping several enhancements particularly targeted towards Arabic searchers and conducting scientific user studies in the region. The research agenda for Project Ibis is primarily in the Information Retrieval and Natural Language Processing fields.

Books remain a very important source of information for knowledge seekers. The ability of searching and browsing through books is key to efficient knowledge acquisition. Unfortunately, many of the books do not exist in digital format, hence not suitable for information retrieval. Efforts for digitizing books are underway in many libraries around the globe with vested interest from big search engines. After undergoing the process of optical character recognition (OCR), books become digitally suitable for text information retrieval engines. The OCR process in many tier 1 language has an acceptable accuracy and hence usable for information retrieval purposes. This is not the case for many non tier 1 languages such as Arabic. In CMIC, we are pursuing a research effort aiming at directly searching within digitized images of book pages rather than searching the OCR resulting text. This is done by transforming the input user query into an image rather than the conventional process of transforming book images into text (OCR). The image-based book search process has the advantage of being language independent, hence readily extendable to other languages.

Online collaborative learning environments have a huge potential to play an important role in education. This is not only limited to distance education and e-learning, but could be carried on to web-enhanced courses. CMIC is currently working on methods to support online learning communities create knowledge. These include enhancing the flow of content within this environment, and methods to evaluate content and knowledge within the learner community. It also investigates the role of social capital and use of social networks within learning communities to enrich the educational outcome. In addition, online collaborative learning environments collect a huge amount of data. This data will be used to evaluate the student contributions, participation and collective knowledge gained within the learner community. The research looks into presenting instructors and students with different viewpoints of the learner community to help with evaluation and self assessment.