Technical description
In the 1960s, mainframe computers were only available within a research context at the university. Within MIT_Computer_Science_and_Artificial_Intelligence_Laboratory#Project_MAC, Project MAC at MIT, the STUDENT system was an early example of a question answering software which uniquely involved natural language processing and symbolic programming. Other early attempts for solving Word problem (mathematics education), algebra story problems were realized with 1960s hardware and software as well: for example, the Philips, Baseball and Synthex systems. STUDENT accepts an algebra story written in the English language as input, and generates a number as output. This is realized with a layered pipeline which consists of Heuristic (computer science), heuristics for pattern transformation. At first, sentences in English are converted into kernel sentences, which each contain a single piece of information. Next, the kernel sentences are converted into mathematical expressions. The knowledge base which supports the transformation contains 52 facts. STUDENT uses a rule-based system with logic inference. The rules are pre-programmed by the software developer and are able to Parsing, parse natural language. More powerful techniques for natural language processing, such as machine learning, came into use later as hardware grew more capable, and gained popularity over simpler rule-based systems.Example
(extracted from Norvig)References