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<Paper uid="H92-1040">
  <Title>APPENDIX: SAMPLE DATA DOCUMENT TEXT: *RECORD*</Title>
  <Section position="12" start_page="209" end_page="209" type="ackno">
    <SectionTitle>
ACKNOWLEDGEMENTS
</SectionTitle>
    <Paragraph position="0"> We would like to thank Donna Harman of NIST for making her IR system available to us. We would also like to thank Ralph Weischedel and Marie Meteer of BBN for providing and assisting in the use of the part of speech tagger. KL Kwok has offered many helpful comments on an earlier draft of this paper. In addition, ACM has generously provided us with text data from the Computer Library database distributed by Ziff Communications Inc. This paper is based upon work supported by the Defense Advanced  2. Mauldin, Michael. 1991. &amp;quot;Retrieval Performance in Ferret: A Conceptual Information Retrieval System.&amp;quot; Proceedings of ACM SIGIR-91, pp. 347-355.</Paragraph>
    <Paragraph position="1"> 3. Sager, Naomi. 1981. Natural Language Information Processing. Addison-Wesley.</Paragraph>
    <Paragraph position="2"> 4. Strzalkowski, Tomek. 1991. &amp;quot;TI'P: A Fast and Robust Parser for Natural Language.&amp;quot; Proteus Project Memo #43, Courant Institute of Mathematical Science, New York University.</Paragraph>
    <Paragraph position="3"> 5. Lewis, David D. and W. Bruce Croft. 1990. &amp;quot;Term Clustering of Syntactic Phrases&amp;quot;. Proceedings of ACM SIGIR-90, pp. 385-405.</Paragraph>
    <Paragraph position="4"> 6. Church, Kenneth Ward and Hanks, Patrick. 1990. &amp;quot;Word association norms, mutual information, and lexicography.&amp;quot; ComputationalLinguistics, 16(1), MIT Press, pp. 22-29.</Paragraph>
    <Paragraph position="5"> 7. Wilks, Yorick A., Dan Fass, Cheng-Ming Guo, James E.</Paragraph>
    <Paragraph position="6"> McDonald, Tony Plate, and Brian M. Slator. 1990. &amp;quot;Providing machine tractable dictionary tools.&amp;quot; Machine Translation, 5, pp. 99-154.</Paragraph>
    <Paragraph position="7"> 8. Sparck Jones, K. and E. O. Barber. 1971. &amp;quot;What makes automatic keyword classification effective?&amp;quot; Journal of the American Society for Information Science, May-June, pp.</Paragraph>
    <Paragraph position="8"> 166-175.</Paragraph>
    <Paragraph position="9"> 9. Crouch, Carolyn J. 1988. &amp;quot;A cluster-based approach to thesaurus construction.&amp;quot; Proceedings of ACM SIGIR-88, pp. 309-320.</Paragraph>
    <Paragraph position="10"> 10. Sparck Jones, K. and J. I. Tait. 1984. &amp;quot;Automatic search term variant generation.&amp;quot; Journal of Documentation, 40(1), pp. 50-66.</Paragraph>
    <Paragraph position="11"> 11. Harrnan, Donna. 1988. &amp;quot;Towards interactive query expansion.&amp;quot; Proceedings ofACM SIGIR-88, pp. 321-331. 12. Sparck Jones, Karen. 1972. &amp;quot;Statistical interpretation of term specificity and its application in retrieval.&amp;quot; Journal of Documentation, 28(1 ), pp. 11-20.</Paragraph>
    <Paragraph position="12"> 13. Croft, W. Bruce, Howard R. Turtle, and David D. Lewis. 1991. &amp;quot;The Use of Phrases and Structured Queries in Information Retrieval.&amp;quot; Proceedings of ACM SIGIR-91, pp. 3245. null 14. Strzalkowski, Tomek and Barbara Vauthey. 1991. &amp;quot;Fast Text Processing for Information Retrieval.&amp;quot; Proceedings of the 4t.h DARPA Speech and Natural Language Workshop, Morgan-Kauffman, pp. 346-351.</Paragraph>
    <Paragraph position="13"> 15. Strzalkowski, Tomek and Barbara Vauthey. 1991. &amp;quot;Natural Language Processing in Automated Information Retrieval.&amp;quot; Proteus Project Memo #42, Courant Institute of Mathematical Science, New York University.</Paragraph>
    <Paragraph position="14"> 16. Grishman, Ralph and Tomek Strzalkowski. 1991. &amp;quot;Information Retrieval and Natural Language Processing.&amp;quot; Position paper at the workshop on Future Dkections in Natural  An algorithm to compute the gamma function and log gamma function of a complex variable is presented.</Paragraph>
    <Paragraph position="15"> The standard algorithm is modified in several respects to insure the continuity of the function value and to reduce accumulation of round-off errors. In addition to computation of function values, this algorithm includes an object-time estimation of round-off errors. Experimental data with regard to the effectiveness of this error control are presented.</Paragraph>
    <Paragraph position="16"> a fortran program for the algorithm appears in the algorithms section of this issue.</Paragraph>
  </Section>
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