| 000 -LEADER |
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| fixed length control field |
08804nam a22007571i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
8424572 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
IEEE |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20200413152926.0 |
| 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 |
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| fixed length control field |
180801s2018 caua foab 000 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781681733937 |
| Qualifying information |
ebook |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| Canceled/invalid ISBN |
9781681733944 |
| Qualifying information |
hardcover |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| Canceled/invalid ISBN |
9781681733920 |
| Qualifying information |
paperback |
| 024 7# - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
10.2200/S00860ED1V01Y201806DMK015 |
| Source of number or code |
doi |
| 035 ## - SYSTEM CONTROL NUMBER |
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| System control number |
(CaBNVSL)swl000408588 |
| 035 ## - SYSTEM CONTROL NUMBER |
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| System control number |
(OCoLC)1047603274 |
| 040 ## - CATALOGING SOURCE |
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| 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 |
QA76.9.D343 |
| Item number |
R455 2018 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.312 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ren, Xiang, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Mining structures of factual knowledge from text : |
| Remainder of title |
an effort-light approach / |
| Statement of responsibility, etc. |
Xiang Ren, Jiawei Han. |
| 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 |
2018. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 PDF (xv, 183 pages) : |
| Other physical details |
illustrations. |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| 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 data mining and knowledge discovery, |
| International Standard Serial Number |
2151-0075 ; |
| Volume/sequential designation |
# 15 |
| 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 167-181). |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1. Introduction -- 1.1 Overview of the book -- 1.1.1 Part I: Identifying typed entities -- 1.1.2 Part II: Extracting typed entity relationships -- 1.1.3 Part III: Toward automated factual structure mining -- 2. Background -- 2.1 Entity structures -- 2.2 Relation structures -- 2.3 Distant supervision from knowledge bases -- 2.4 Mining entity and relation structures -- 2.5 Common notations -- 3. Literature review -- 3.1 Hand-crafted methods -- 3.2 Traditional supervised learning methods -- 3.2.1 Sequence labeling methods -- 3.2.2 Supervised relation extraction methods -- 3.3 Weakly supervised extraction methods -- 3.3.1 Semi-supervised learning -- 3.3.2 Pattern-based bootstrapping -- 3.4 Distantly supervised learning methods -- 3.5 Learning with noisy labeled data -- 3.6 Open-domain information extraction -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part I. Identifying typed entities -- 4. Entity recognition and typing with knowledge bases -- 4.1 Overview and motivation -- 4.2 Problem definition -- 4.3 Relation phrase-based graph construction -- 4.3.1 Candidate generation -- 4.3.2 Mention-name subgraph -- 4.3.3 Name-relation phrase subgraph -- 4.3.4 Mention correlation subgraph -- 4.4 Clustering-integrated type propagation on graphs -- 4.4.1 Seed mention generation -- 4.4.2 Relation phrase clustering -- 4.4.3 The joint optimization problem -- 4.4.4 The ClusType algorithm -- 4.4.5 Computational complexity analysis -- 4.5 Experiments -- 4.5.1 Data preparation -- 4.5.2 Experimental settings -- 4.5.3 Experiments and performance study -- 4.6 Discussion -- 4.7 Summary -- 5. Fine-grained entity typing with knowledge bases -- 5.1 Overview and motivation -- 5.2 Preliminaries -- 5.3 The AFET framework -- 5.3.1 Text feature generation -- 5.3.2 Training set partition -- 5.3.3 The joint mention-type model -- 5.3.4 Modeling type correlation -- 5.3.5 Modeling noisy type labels -- 5.3.6 Hierarchical partial-label embedding -- 5.4 Experiments -- 5.4.1 Data preparation -- 5.4.2 Evaluation settings -- 5.4.3 Performance comparison and analyses -- 5.5 Discussion and case analysis -- 5.6 Summary -- 6. Synonym discovery from large corpus / Meng Qu -- 6.1 Overview and motivation -- 6.1.1 Challenges -- 6.1.2 Proposed solution -- 6.2 The DPE framework -- 6.2.1 Synonym seed collection -- 6.2.2 Joint optimization problem -- 6.2.3 Distributional module -- 6.2.4 Pattern module -- 6.3 Experiment -- 6.4 Summary -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part II. Extracting typed relationships -- 7. Joint extraction of typed entities and relationships -- 7.1 Overview and motivation -- 7.2 Preliminaries -- 7.3 The CoType framework -- 7.3.1 Candidate generation -- 7.3.2 Joint entity and relation embedding -- 7.3.3 Model learning and type inference -- 7.4 Experiments -- 7.4.1 Data preparation and experiment setting -- 7.4.2 Experiments and performance study -- 7.5 Discussion -- 7.6 Summary -- 8. Pattern-enhanced embedding learning for relation extraction / Meng Qu -- 8.1 Overview and motivation -- 8.1.1 Challenges -- 8.1.2 Proposed solution -- 8.2 The REPEL framework -- 8.3 Experiment -- 8.4 Summary -- 9. Heterogeneous supervision for relation extraction / Liyuan Liu -- 9.1 Overview and motivation -- 9.2 Preliminaries -- 9.2.1 Relation extraction -- 9.2.2 Heterogeneous supervision -- 9.2.3 Problem definition -- 9.3 The REHession framework -- 9.3.1 Modeling relation mention -- 9.3.2 True label discovery -- 9.3.3 Modeling relation type -- 9.3.4 Model learning -- 9.3.5 Relation type inference -- 9.4 Experiments -- 9.5 Summary -- 10. Indirect supervision: leveraging knowledge from auxiliary tasks / Zeqiu Wu -- 10.1 Overview and motivation -- 10.1.1 Challenges -- 10.1.2 Proposed solution -- 10.2 The proposed approach -- 10.2.1 Heterogeneous network construction -- 10.2.2 Joint RE and QA embedding -- 10.2.3 Type inference -- 10.3 Experiments -- 10.4 Summary -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part III. Toward automated factual structure mining -- 11. Mining entity attribute values with meta patterns / Meng Jiang -- 11.1 Overview and motivation -- 11.1.1 Challenges -- 11.1.2 Proposed solution -- 11.1.3 Problem formulation -- 11.2 The MetaPAD framework -- 11.2.1 Generating meta patterns by context-aware segmentation -- 11.2.2 Grouping synonymous meta patterns -- 11.2.3 Adjusting type levels for preciseness -- 11.3 Summary -- 12. Open information extraction with global structure cohesiveness / Qi Zhu -- 12.1 Overview and motivation -- 12.1.1 Proposed solution -- 12.2 The ReMine framework -- 12.2.1 The joint optimization problem -- 12.3 Summary -- 13. Applications -- 13.1 Structuring life science papers: the Life-iNet system -- 13.2 Extracting document facets from technical corpora -- 13.3 Comparative document analysis -- 14. Conclusions -- 14.1 Effort-light StructMine: summary -- 14.2 Conclusion -- 15. Vision and future work -- 15.1 Extracting implicit patterns from massive unlabeled corpora -- 15.2 Enriching factual structure representation -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Bibliography -- Authors' biographies. |
| 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. |
The real-world data, though massive, is largely unstructured, in the form of natural-language text. It is challenging but highly desirable to mine structures from massive text data, without extensive human annotation and labeling. In this book, we investigate the principles and methodologies of mining structures of factual knowledge (e.g., entities and their relationships) from massive, unstructured text corpora. Departing from many existing structure extraction methods that have heavy reliance on human annotated data for model training, our effort-light approach leverages human-curated facts stored in external knowledge bases as distant supervision and exploits rich data redundancy in large text corpora for context understanding. This effort-light mining approach leads to a series of new principles and powerful methodologies for structuring text corpora, including: (1) entity recognition, typing, and synonym discovery; (2) entity relation extraction; and (3) open-domain attribute-value mining and information extraction. This book introduces this new research frontier and points out some promising research directions. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
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| 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 August 1, 2018). |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Electronic information resource searching. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data structures (Computer science) |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
mining factual structures |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
information extraction |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
knowledge bases |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
entity recognition and typing |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
relation extraction |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
entity synonym mining |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
distant supervision |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
effort-light approach |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
classification |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
clustering |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
real-world applications |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
scalable algorithms |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Han, Jiawei, |
| Relator term |
author. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| International Standard Book Number |
9781681733920 |
| -- |
9781681733944 |
| 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 data mining and knowledge discovery ; |
| Volume/sequential designation |
# 15. |
| International Standard Serial Number |
2151-0075 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Abstract with links to resource |
| Uniform Resource Identifier |
https://ieeexplore.ieee.org/servlet/opac?bknumber=8424572 |
