A generative theory of relevance
This book presents a new way to look at topical relevance in information retrieval and offers a new method for modeling exchangeable sequences of discrete random variables which does not make any assumptions about the data and can also handle rare events.
| Main Author: | Lavrenko, Victor. |
|---|---|
| Other Authors: | SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Berlin :
Springer-Verlag,
©2009.
Berlin : [2009] |
| Physical Description: |
1 online resource. |
| Series: |
Information retrieval series ;
vol. 26. |
| Subjects: |
| Summary: |
This book presents a new way to look at topical relevance in information retrieval and offers a new method for modeling exchangeable sequences of discrete random variables which does not make any assumptions about the data and can also handle rare events. |
|---|---|
| Item Description: |
Includes bibliographical references and index. Introduction -- Relevance -- A generative view of relevance -- Generative density allocation -- Retrieval scenarios -- Conclusion. This book presents a new way to look at topical relevance in information retrieval and offers a new method for modeling exchangeable sequences of discrete random variables which does not make any assumptions about the data and can also handle rare events. University staff and students only. Requires University Computer Account login off-campus. |
| Physical Description: |
1 online resource. |
| Bibliography: |
Includes bibliographical references and index. |
| ISBN: |
9783540893646 3540893644 |
| Access: |
University staff and students only. Requires University Computer Account login off-campus. |