Development of the coder system: A testbed for artificial intelligence methods in information retrieval

摘要

The CODER (Composite Document Expert/Extended/Effective Retrieval) system is a testbed for investigating the application of artificial intelligence methods to increase the effectiveness of information retrieval systems. Particular attention is being given to analysis and representation of heterogeneous documents, such as electronic mail digests or messages, which vary widely in style, length, topic, and structure. Since handling passages of various types in these collections is difficult even for experimental systems like SMART, it is necessary to turn to other techniques being explored by information retrieval and artificial intelligence researchers. The CODER system architecture involves communities of experts around active blackboards, accessing knowledge bases that describe users, documents, and lexical items of various types. The initial lexical knowledge base construction work is now complete, and experts for search and time/date handling can perform a variety of processing tasks. User information and queries are being gathered, and a simple distributed skeletal system is operational. It appears that a number of artificial intelligence techniques are needed to best handle such common but complex document analysis and retrieval tasks.