| 000 -LEADER |
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| fixed length control field |
06913nam a22007091i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
8585440 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
IEEE |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20200413152928.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
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| fixed length control field |
m eo d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr cn |||m|||a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
190103s2019 caua foab 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781681734736 |
| Qualifying information |
ebook |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781681734743 |
| Qualifying information |
hardcover |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781681734729 |
| Qualifying information |
paperback |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.2200/S00887ED1V01Y201811ICR065 |
| Source of number or code |
doi |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(CaBNVSL)swl000408884 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)1080937311 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
CaBNVSL |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
CaBNVSL |
| Modifying agency |
CaBNVSL |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
ZA3075 |
| Item number |
.L676 2019 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
028.7071 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Losee, Robert M. |
| Fuller form of name |
(Robert MacLean), |
| Dates associated with a name |
1952-, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Predicting information retrieval performance / |
| Statement of responsibility, etc. |
Robert M. Losee. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
[San Rafael, California] : |
| Name of producer, publisher, distributor, manufacturer |
Morgan & Claypool, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2019. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 PDF (xix, 59 pages) : |
| Other physical details |
illustrations. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
electronic |
| Source |
isbdmedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Source |
rdacarrier |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Synthesis lectures on information concepts, retrieval, and services, |
| International Standard Serial Number |
1947-9468 ; |
| Volume/sequential designation |
# 65 |
| 538 ## - SYSTEM DETAILS NOTE |
|---|
| System details note |
Mode of access: World Wide Web. |
| 538 ## - SYSTEM DETAILS NOTE |
|---|
| System details note |
System requirements: Adobe Acrobat Reader. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Part of: Synthesis digital library of engineering and computer science. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references (pages 57-58). |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1. Information retrieval: a predictive science -- 1.1 Rules, measures, and science -- 1.2 The science of information retrieval -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
2. Probabilities and probabilistic information retrieval -- 2.1 Probabilities -- 2.2 Probabilistic retrieval -- 2.2.1 Bayes rule -- 2.3 Describing a probability -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
3. Information retrieval performance measures -- 3.1 Precision and recall -- 3.1.1 Precision -- 3.1.2 Recall -- 3.2 Precision-recall graphs -- 3.2.1 High-precision systems and high-recall systems -- 3.2.2 Generality and fallout -- 3.3 High-precision performance measures -- 3.3.1 Mean average precision -- 3.3.2 Precision at k -- 3.3.3 Discounted cumulative gain -- 3.3.4 F measure -- 3.3.5 Mean reciprocal rank -- 3.4 Receiver operating characteristic -- 3.5 Search lengths -- 3.5.1 Expected search length -- 3.5.2 Average search length and the expected position of a relevant document -- 3.6 Summary -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
4. Single-term performance -- 4.1 A single binary term -- 4.2 Average search length and expected position of a relevant document -- 4.3 Probability of optimal ranking (Q) -- 4.3.1 Developing Q -- 4.3.2 Best-case ranking -- 4.3.3 Interpreting Pr(p > t) -- 4.3.4 Worst-case ranking -- 4.3.5 Random ranking -- 4.3.6 Q and ranking by inverse document frequency weighting -- 4.3.7 Q and ranking by decision-theoretic weighting -- 4.4 Expected position of a relevant document given Q and A values -- 4.4.1 Best- and worst-case performance -- 4.5 General discrete single feature distribution models -- 4.5.1 Binary feature model -- 4.5.2 A single Poisson feature -- 4.6 General continuous feature distribution models -- 4.6.1 Normal distribution -- 4.7 Advanced models of Q -- 4.7.1 Point probabilities -- 4.7.2 Distribution instead of a point probability -- 4.7.3 Inaccurate knowledge about a distribution -- 4.8 Predicting performance with high precision retrieval -- 4.8.1 A changing for different segments of an ordering -- 4.9 Summary -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
5. Performance with multiple binary features -- 5.1 Partial dependence -- 5.1.1 Maximum spanning tree -- 5.1.2 Simple maximum spanning trees -- 5.1.3 Partial dependencies with Bahadur Lazarsfeld and generalized dependence models -- 5.2 Singular value decomposition -- 5.3 Teugels' models for full dependence -- 5.3.1 Covariances to probabilities -- 5.3.2 Averages to probabilities -- 5.3.3 Probabilities to covariances -- 5.3.4 Probabilities to averages -- 5.4 Example with documents -- 5.5 Predicting performance with feature dependence -- 5.6 Validation -- 5.7 Feature independence -- 5.8 Summary -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
6. Applications: metadata and linguistic labels -- 6.1 Metadata and indexing -- 6.1.1 Assigning terms to relevant documents -- 6.1.2 Not assigning terms to relevant documents -- 6.1.3 Not assigning terms to non-relevant documents -- 6.1.4 Incorrectly assigning terms to non-relevant document -- 6.2 Validating metadata rules -- 6.3 Natural language part-of-speech tags -- 6.3.1 Best- and worst-case performance with tags -- 6.4 Summary -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
7. Conclusion -- A. Variables -- Bibliography -- Author's biography. |
| 506 ## - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Abstract freely available; full-text restricted to subscribers or individual document purchasers. |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Compendex |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
INSPEC |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Google scholar |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Google book search |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively. This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
|---|
| Additional physical form available note |
Also available in print. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Title from PDF title page (viewed on January 3, 2019). |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Information retrieval |
| General subdivision |
Evaluation. |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Information Retrieval |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
performance measures |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
science |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
predicting performance |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
single term models |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
statistical feature dependence |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
multiple features |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
metadata performance |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
natural language performance measures |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| International Standard Book Number |
9781681734729 |
| -- |
9781681734743 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Synthesis digital library of engineering and computer science. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Synthesis lectures on information concepts, retrieval, and services ; |
| Volume/sequential designation |
# 65. |
| International Standard Serial Number |
1947-9468 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Abstract with links to resource |
| Uniform Resource Identifier |
https://ieeexplore.ieee.org/servlet/opac?bknumber=8585440 |
