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| 003 - CONTROL NUMBER IDENTIFIER |
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OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20140310151114.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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130331s2013 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781461468950 |
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978-1-4614-6895-0 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9.D343 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.312 |
| Edition number |
23 |
| 264 #1 - |
|---|
| -- |
New York, NY : |
| -- |
Springer New York : |
| -- |
Imprint: Springer, |
| -- |
2013. |
| 912 ## - |
|---|
| -- |
ZDB-2-SCS |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Bhuiyan, Touhid. |
| Relator term |
author. |
| 245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Title |
Trust for Intelligent Recommendation |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc |
by Touhid Bhuiyan. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XIV, 119 p. 34 illus. |
| Other physical details |
online resource. |
| 440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
SpringerBriefs in Electrical and Computer Engineering, |
| International Standard Serial Number |
2191-8112 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Introduction -- Literature Review -- Trust Inferences using Subjective Logic -- Online Survey on Trust and Interest Similarity -- SimTrust: The Algorithm for Similarity-based Trust Network Generation -- Experiments and Evaluation -- Conclusions -- Appendix A: Sample Survey Questions -- Appendix B: Glossary of Terms and Abbreviations -- Appendix C: Combining Trust & Reputation Management. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Recommender systems are one of the recent inventions to deal with the ever-growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbors, generated from a database made up of the preferences of past users. In the absence of these ratings, trust between the users could be used to choose the neighbor for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world “friend of a friend” recommendations. To extend the boundaries of the neighbor, an effective trust inference technique is required. This book proposes a trust interference technique called Directed Series Parallel Graph (DSPG) that has empirically outperformed other popular trust inference algorithms, such as TidalTrust and MoleTrust. For times when reliable explicit trust data is not available, this book outlines a new method called SimTrust for developing trust networks based on a user’s interest similarity. To identify the interest similarity, a user’s personalized tagging information is used. However, particular emphasis is given in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbors used in the automated recommender system. Through a series of case studies and empirical results, this book highlights the effectiveness of this tag-similarity based method over the traditional collaborative filtering approach, which typically uses rating data. Trust for Intelligent Recommendation is intended for practitioners as a reference guide for developing improved, trust-based recommender systems. Researchers in a related field will also find this book valuable. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer science. |
|
|---|
| Topical term or geographic name as entry element |
Data mining. |
|
|---|
| Topical term or geographic name as entry element |
Artificial intelligence. |
|
|---|
| Topical term or geographic name as entry element |
Computer Science. |
|
|---|
| Topical term or geographic name as entry element |
Data Mining and Knowledge Discovery. |
|
|---|
| Topical term or geographic name as entry element |
Information Systems Applications (incl. Internet). |
|
|---|
| Topical term or geographic name as entry element |
Artificial Intelligence (incl. Robotics). |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9781461468943 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-1-4614-6895-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
E-Book |
