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- Quantification in Query Systems
- Annual ACM Conference on Research and Development in Information Retrieval (Proceedings of the 1971 international ACM SIGIR conference on Information storage and retrieval, College Park, Maryland) pp. 81-93. ACM
Questions which involve 'all', 'every', 'some', or the indefinite article, pose some peculiar problems when presented to a computerized question-answering system where ambiguities cannot be tolerated. These problems vary from the nature of the correct answer in special cases to the very admissibility of the question itself. To deal with these problems it is convenient to divide questions into two classes---extensional questions whose answers are to name things or truth values, intensional questions whose answers are to give meanings. This paper examines extensional questions. For these, the interpretative problems arising with 'all' and 'every' can be solved by introducing a new kind of quantification, extensional universal quantification, that has the meaning of 'all F' together with a secondary meaning that the class F is not empty. Formal rules for this quantification are given, and it is shown that the so-called definite formulas (which explicate permissible queries) are closed under the new operator.
- M.E. Maron (1977) mentioning objective and subjective aboutness.
- R.A. Fairthorne (1969) mentioning extensional and intensional aboutness.
- A Theory of Justice
- revised in 1975 (for the translated eds.) and 1999
- revised in 2001 as Justice as Fairness (2001)
- The SMART Retrieval System: Experiments in Automatic Document Processing
- Prentice-Hall, Inc., Eaglewood Cliffs, NJ, 1971.
The automatic SMART document retrieval system was designed at Harvard University between 1961 and 1964, and has been operating on IBM 7094 and 360 equipment at Harvard and at Cornell University for several years. The system takes documents and search requests in the natural language, performs a fully automatic content analysis of the texts using one of several dozen programmed language analysis methods, and matches analyzed documents with analyzed search requests, and retrieves for the user's attention those stored items believed to be most similar to the submitted queries.
Unlike the other computer-based retrieval systems, the SMART system does not rely on manually assigned keywords or index terms for the identification of documents and search requests,nor does it use primarily the frequency occurrence of certain words or phrases included in the texts of documents. Instead, an attempt is made to go beyond simple word-matching procedures by using a variety of intellectual aids in the form of synonym dictionaries, hierarchical arrangements of subject identifiers, statistical and syntactic phrase generation methods, and the like, in order to obtain content identifications useful for the retrieval process.
By comparing the retrieval performance obtained with the various programmed procedures, the SMART system can be used as a unique experimental tool for the evaluation in a controlled laboratory environment of many fully automatic language analysis methods. In addition, the system has been used to simulate a user-environment by making it possible for the user to participate in the search process. Specifically, the system utilizes feedback information supplied by the user during the search to construct improved search formulations, and to generate document representations reflecting the interests of the user population. By combining automatic text processing methods with interactive search and retrieval techniques, the SMART system may then lead to the design and implementation of modern information services of the type which may become current in operational environments some years hence. (pp. vii-viii)