| 000 | 00940camuu2200277 a 4500 | |
| 001 | 000045687717 | |
| 005 | 20120126175210 | |
| 008 | 120126s2011 nyu b 001 0 eng d | |
| 010 | ▼a 2010021870 | |
| 020 | ▼a 9780521493369 (hardback) | |
| 020 | ▼a 0521493366 (hardback) | |
| 035 | ▼a (KERIS)REF000016210686 | |
| 040 | ▼a DLC ▼c DLC ▼d CDX ▼d YDXCP ▼d DLC ▼d 211009 | |
| 050 | 0 0 | ▼a TK5103.485 ▼b .R43 2011 |
| 082 | 0 0 | ▼a 006.3/3 ▼2 22 |
| 084 | ▼a 006.33 ▼2 DDCK | |
| 090 | ▼a 006.33 ▼b R311 | |
| 245 | 0 0 | ▼a Recommender systems : ▼b an introduction / ▼c Dietmar Jannach ... [et al.]. |
| 260 | ▼a New York : ▼b Cambridge University Press, ▼c 2011. | |
| 300 | ▼a 335 p. ; ▼c 24 cm. | |
| 504 | ▼a Includes bibliographical references and index. | |
| 650 | 0 | ▼a Personal communication service systems. |
| 650 | 0 | ▼a Recommender systems (Information filtering) |
| 700 | 1 | ▼a Jannach, Dietmar, ▼d 1973-. |
| 945 | ▼a KLPA |
소장정보
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.33 R311 | 등록번호 121216532 (13회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. 2 | 소장처 세종학술정보원/과학기술실(5층)/ | 청구기호 006.33 R311 | 등록번호 151313231 (6회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 과학도서관/Sci-Info(2층서고)/ | 청구기호 006.33 R311 | 등록번호 121216532 (13회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
| No. | 소장처 | 청구기호 | 등록번호 | 도서상태 | 반납예정일 | 예약 | 서비스 |
|---|---|---|---|---|---|---|---|
| No. 1 | 소장처 세종학술정보원/과학기술실(5층)/ | 청구기호 006.33 R311 | 등록번호 151313231 (6회 대출) | 도서상태 대출가능 | 반납예정일 | 예약 | 서비스 |
컨텐츠정보
책소개
This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations.
In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems. This book offers an overview of approaches to developing state-of-the-art recommender systems that automate a variety of choice-making strategies with the goal of providing affordable, personal, and high-quality recommendations. The authors present algorithmic approaches for generating personalized buying proposals, as well as more interactive and knowledge-based approaches. They discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies.
정보제공 :
목차
1. Introduction; Part I. Introduction into Basic Concepts: 2. Collaborative recommendation; 3. Content-based recommendation; 4. Knowledge-based recommendation; 5. Hybrid recommendation approaches; 6. Explanations in recommender systems; 7. Evaluating recommender systems; 8. Case study - personalized game recommendations on the mobile Internet; Part II. Recent Developments: 9. Attacks on collaborative recommender systems; 10. Online consumer decision making; 11. Recommender systems and the next-generation Web; 12. Recommendations in ubiquitous environments; 13. Summary and outlook.
정보제공 :