On reasoning from data
David L. Waltz, Simon Kasif · ACM Computing Surveys · 1995
Introduction Our society is currently entering a new phase where gigabytes of information are being generated, and are becoming readily available for exploration over academic networks, digital libraries, and commercial information services as well as in proprietary commercial and governmental databases. This important technological development presents a substantial challenge, as future intelligent systems must be able to store very large streams of data, summarize and index this data using concise and efficient models and subsequently perform very efficient retrieval and reasoning in response to real-time queries and updates. We informally refer to this challenging task as reasoning from data. Most previous AI research and applications have concentrated on relatively simple operations, e.g., highly constrained queries on relatively static, immutable systems of knowledge -- e.g., mathematics; chess; hardware components inventories; -- where it is possible to