Book Search Experiments: Investigating IR Methods for the Indexing and Retrieval of Books

Wu, Hengzhi; Kazai, Gabriella; Taylor, Michael

doi:10.1007/978-3-540-78646-7_23

Cited by 9 publications

(4 citation statements)

References 9 publications

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“…Wu et al in [28], for example, investigate the relative effectiveness of different types of book specific data, such as table of contents, back of book indexes, footnotes, and bibliography, using a multifield inverted index. They show that table of contents and back of book indexes are prominent features for estimating relevance in book retrieval.…”

Section: Books As a New Vertical In Searchmentioning

confidence: 99%

Wikipedia pages as entry points for book search

Koolen

Kazai

Craswell

2009

Proceedings of the Second ACM International Conference on Web Search and Data Mining

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A lot of the world's knowledge is stored in books, which, as a result of recent mass-digitisation efforts, are increasingly available online. Search engines, such as Google Books, provide mechanisms for searchers to enter this vast knowledge space using queries as entry points. In this paper, we view Wikipedia as a summary of this world knowledge and aim to use this resource to guide users to relevant books. Thus, we investigate possible ways of using Wikipedia as an intermediary between the user's query and a collection of books being searched. We experiment with traditional query expansion techniques, exploiting Wikipedia articles as rich sources of information that can augment the user's query. We then propose a novel approach based on link distance in an extended Wikipedia graph: we associate books with Wikipedia pages that cite these books and use the link distance between these nodes and the pages that match the user query as an estimation of a book's relevance to the query. Our results show that a) classical query expansion using terms extracted from query pages leads to increased precision, and b) link distance between query and book pages in Wikipedia provides a good indicator of relevance that can boost the retrieval score of relevant books in the result ranking of a book search engine.

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Section: Books As a New Vertical In Searchmentioning

confidence: 99%

Wikipedia pages as entry points for book search

Koolen

Kazai

Craswell

2009

Proceedings of the Second ACM International Conference on Web Search and Data Mining

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“…BM25F has also been used for XML-encoded book retrieval, where the task was to return books not elements [7,16] producing 9.09% improvement measured by NDCG@1.…”

Section: Bm25fmentioning

confidence: 99%

A framework for BM25F-based XML retrieval

Itakura

Clarke

2010

Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval

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We evaluate a framework for BM25F-based XML element retrieval. The framework gathers contextual information associated with each XML element into an associated field, which we call a characteristic field. The contents of the element and the contents of the characteristic field are then treated as distinct fields for BM25F weighting purposes. Evidence supporting this framework is drawn from both our own experiments and experiments reported in related work.

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“…We rank the venues based on the number of "cited by" books and list the top 20 of them in Table 10, with the IF (2009) and h-index shown in the fourth and fifth column for each venue. The IF value is queried using MedSci 25 relying on ISI and the h-index is from SCIMAGO 26 based on scopus 27 . The results shown in Table 10 offer several interesting observations.…”

Section: Venue Rankmentioning

confidence: 99%

“…H. Wu et al reported an experimental book search system that supports both database and IR style index structures. Their findings suggest that fielded retrieval is a suitable strategy to apply to collections of books [27]. W. Magdy et al examined the effect of indexing different parts of digitized books on retrieval in response to specific information needs.…”

Section: Book Search and Retrievalmentioning

confidence: 99%

Searching online book documents and analyzing book citations

Das

et al. 2013

Proceedings of the 2013 ACM Symposium on Document Engineering

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Academic search engines and digital libraries provide convenient online search and access facilities for scientific publications. However, most existing systems do not include books in their collections although several books are freely available online. Academic books are different from papers in terms of their length, contents and structure. We argue that accounting for academic books is important in understanding and assessing scientific impact. We introduce an open-book search engine that extracts and indexes metadata, contents, and bibliography from online PDF book documents. To the best of our knowledge, no previous work gives a systematical study on building a search engine for books.We propose a hybrid approach for extracting title and authors from a book that combines results from CiteSeer, a rule based extractor, and a SVM based extractor, leveraging web knowledge. For "table of contents" recognition, we propose rules based on multiple regularities based on numbering and ordering. In addition, we study bibliography extraction and citation parsing for a large dataset of books. Finally, we use the multiple fields available in books to rank books in response to search queries. Our system can effectively extract metadata and contents from large collections of online books and provides efficient book search and retrieval facilities.

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Book Search Experiments: Investigating IR Methods for the Indexing and Retrieval of Books

Cited by 9 publications

References 9 publications

Wikipedia pages as entry points for book search

Wikipedia pages as entry points for book search

A framework for BM25F-based XML retrieval

Searching online book documents and analyzing book citations

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