With the proliferation of Web 2.0, social tag is widely used in various applications. Online bookstores (like Amazon) and online bibliographic community Websites (like LibraryThing) have quickly accumulated a large amount of user-generated information. INEX (INitiative for the Evaluation of XML retrieval) have been using the Amazon/LibraryThing corpus for its Social Book Search Track since 2011. The purpose of the INEX Social Book Search Track is to develop novel algorithms leveraging professional metadata and user-generated metadata for effectively retrieving books. This thesis uses INEX 2013 Social Book Search Track test data set to conduct book search experiments and evaluate the retrieval results. Indices based on professional metadata, user-generated metadata and both are created respectively.
The results of this study are summarized as follows: Using social data in the probabilistic retrieval model for Book Search outperforms using traditional bibliographic data. Using all book data including reviews in the probabilistic retrieval model for Book Search can get the best retrieval performance. Using social tag information in the probabilistic retrieval model for Book Search has no significant difference with traditional bibliographic data, but using the number of times a tag used as weight to retrieval can improve the retrieval performance. Using reviews data for re-ranking can achieve the best search results in this study; it can improve 3.1% of the nDCG scores. Using tag data for reranking can improve 25% of the nDCG score. Practically, the results of this thesis can be used as a clue for the design of a book search system and a book recommendations system.
|Advisor:||Locks, Angela M.|
|Commitee:||Ortiz, Anna M., Oseguera, Leticia|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 54/05M(E), Masters Abstracts International|
|Subjects:||Science education, Higher education|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be