We offer a quick way to compare the prices of any in-print and many out-of-print books at over a dozen online bookstores. You can view the results with or without the shipping costs of a single book, and also find the fastest source for a book from ordering to delivery.
Discover more than one million documents from scholarly journals, magazines, conference proceedings, and other special publications from prestigious scientific societies and technical publishers.
The Google Book Search Dynamic Links feature allows you to create more customizable, reliable links to Google Book Search from your site. For example, this tool lets you generate "smart" links that appear only when a book is in our index, or display links that indicate to your users whether a book can be previewed on Google Book Search. The Dynamic Links feature also lets you include a thumbnail image in your link to Google Book Search. This document is intended to let you quickly add this functionality to your site.
CrossRef Search
In order to open published scholarly content for the first time to free, full-text interpublisher searchability, a group of 29 leading journal publishers are participating in a CrossRef Search Pilot.
Through a special, reciprocal arrangement between Google and CrossRef, this Pilot launches a typical Google search but filters the result set to the scholarly research content from participating publishers, with the intent of reducing the noise produced by general web searches.
Google has indexed the full text of scholarly journal articles on the publishers' websites through a CrossRef gateway. Users may submit searches from CrossRef Search Pilot boxes on participating publishers' sites. Results are returned from Google using the Google search and ranking algorithms, and using the article's DOI whenever possible to link from the search results to the published article.
Specify your canonical
Thursday, February 12, 2009 at 12:30 PM
Carpe diem on any duplicate content worries: we now support a format that allows you to publicly specify your preferred version of a URL. If your site has identical or vastly similar content that's accessible through multiple URLs, this format provides you with more control over the URL returned in search results. It also helps to make sure that properties such as link popularity are consolidated to your preferred version
STATISTICAL STRATEGIES ENVIRONMENTAL EPIDEMIOLOGY
report is in. three parts, general problems in environmental epidemiology,. prototypical. problems, and statistical strategies. Emphasis ...
projecteuclid.org/DPubS/Repository/1.0/Disseminate?handle=euclid.bsmsp/1200514698&view=body&content-type=pdf_1 - Similar pages -
by JR GOLDSMITH - Related articles - All 2 versions
How is the indexing performed?
A: Indexing is the process of creating a Conceptual Fingerprint from a text. In Collexis, this automated indexing mechanism performs the following steps on the text: removing the stop words, normalizing the text, selecting concepts by comparison with the thesaurus, clustering the concepts and attaching a relative weight to the concepts by means of a set of algorithms and measuring the specificity, similarity and frequency of the concepts.
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Q: How does Collexis generate its search results?
A: Collexis employs vector matching: comparing a search query with the Fingerprints from the records in a Collexion. The outcome is a very accurate and relevant list of content items and/or experts in the form of a list of records. There also exists the possibility of over-specifying a query (i.e., using a considerable piece of text), thus adding context to the query. This context will help the system to improve the accuracy of the query and return references to those content items that are contextually related. The system administrator can enlarge or reduce the set of returned documents by entering a threshold that indicates the minimum “distance” between the records returned and the query. Matching of a search query with Collexion records can be performed on multiple Collexions at the same time.
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Q: What makes Collexis different?
A: Initially, Collexis differentiates itself from full-text search engines by making use of thesauri for information retrieval. The high-quality search is based on semantics that have been defined in a thesaurus or ontology: synonymous terms and terms in different languages are linked to a single concept. Hierarchical relations between concepts, links between definitions and terms, and other semantic relationships are utilized in the search applications. This process helps to highlight those terms most relevant to the searcher’s query.
Collexis High Definition Search enables fast, accurate and extraordinary knowledge retrieval and discovery quickly and accurately by utilizing fingerprinting technology. The Collexis Fingerprint empowers users to identify and search for documents, experts, trends, and new discoveries more quickly, precisely – and thoroughly – than conventional search engines. For users, the savings in research dollars are extraordinary. High Definition Search positions Collexis as a world leader in the vital area of knowledge management and discovery software.
Text Search
Graphs With Text
Types of Things With Text
People With Shared Interests
Interests Around
Top 100 Authors by Text
Social Connections a la LinkedIn
Connection Between
Cloud Around Person
The FacetedDBLP search interface allows to search computer science publications in the DBLP collection starting from some keyword and shows the result set along with a set of facets, e.g., distinguishing publication years, authors, or conferences. It is the first large scale application that uses GrowBag graphs to create a computer science specific topic facet, with which a user can characterize the result set in terms of main research topics and filter it according to certain subtopics.
FacetedDBLP builds upon the DBLP++ data set which is an enhancement of DBLP (as of 2008-11-21) plus additional keywords and abstracts as available on public web pages. We have also corrected some of the links to electronic editions, which were broken in DBLP. A brief description of the GrowBag facet within FacetedDBLP can be found in our JCDL paper, a detailed description of the algorithm is available on the GrowBag project page.
OpenDOAR is an authoritative directory of academic open access repositories. Each OpenDOAR repository has been visited by project staff to check the information that is recorded here. This in-depth approach does not rely on automated analysis and gives a quality-controlled list of repositories.
This form allows you to retrieve Digital Object Identifiers (DOIs) for journal articles, books, and chapters by simply cutting and pasting the reference list into the box below. You may use the form with any reference style, although the tool works most reliably if references are formatted in a standard style such as shown in this example:
CrossRef currently provides three ways for you to locate a DOI.
* If you have bibliographic data for a item and would like to find the DOI, please use the metadata section of this form.
* If you only have an article title and author, please use the article title search section of this form.
* If you have the text of a bibliographic reference, please use our automatic parsing service described at the bottom of this page.
Open Source Discovery Portal Camp
Join the development teams from VuFind and Blacklight at PALINET, November 6, 2008, for day of discussion and sharing. We hope to examine difficult issues in developing discovery systems, such as:
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ILS Connectivity
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Authority Control
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Data Importing
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User Interface Issues
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Federated Search
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Virtual shelf list
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De-dupping
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Usage Recording and Reporting
Implementing or hacking an Open Source discovery system such as VuFind or Blacklight?
Interested in learning more about Lucene/Solr applications?
Join the development teams from VuFind and Blacklight at PALINET, November 6, 2008, for day of discussion and sharing. We hope to examine difficult issues in developing discovery systems, such as:
*
ILS Connectivity
*
Authority Control
*
Data Importing
*
User Interface Issues
*
Federated Search
*
Virtual shelf list
*
De-dupping
*
Usage Recording and Reporting
Principles of categorized search result visualization
We are developing a set of search result visualization principles, based on the premise that consistent, comprehensible visual displays built on meaningful and stable classifications will better support user understanding of search results.
1. Provide overviews of large sets of results (100-1000+)
2. Organize overviews around meaningful categories
3. Clarify and visualize category structure
4. Tightly couple category labels to result list
5. Ensure that the full category information is available
6. Support multiple types of categories and visual presentations
7. Use separate facets for each type of category
8. Arrange text for scanning/skimming
9. Visually encode quantitative attributes on a stable visual structure
The time has come for libraries, too, to negotiate for rights to index full text
By Jonathan Rochkind -- Library Journal, 2/15/2007
The ability to search and receive results in more than one database through a single interface—or metasearch—is something many of our users want. Google Scholar—the search engine of specifically scholarly content—and library metasearch products like Ex Libris's MetaLib, Serials Solution's Central Search, WebFeat, and products based on MuseGlobal used by both academic and public libraries—are all a means of providing this functionality. At the university where I work, without very much local advertising, Google Scholar has become the largest single source of links to our link resolver product, illustrating how hungry users are for metasearch.
DYNAMIC REFERENCE SIFTING: A CASE STUDY IN THE HOMEPAGE DOMAIN
Jonathan Shakes, Marc Langheinrich & Oren Etzioni
Department of Computer Science and Engineering
University of Washington
Seattle, Washington 98195-2350, USA
{jshakes|marclang|etzioni}@cs.washington.edu
(in Proceedings of the Sixth International World Wide Web Conference, pp.189-200, 1997)
SumoBrain is FREE! SumoBrain offers cross-collection searching, portfolios, alerts, and other collaboration tools, as well as bulk PDF download capabilities. Sumobrain caters to intellectual property professionals, attorneys, and users in the corporate world. While SumoBrain was conceived as a subscription service, we have decided to take the radical step of making SumoBrain completely free. As long as we can support its costs without subscription fees, it will remain free indefinitely
BOSS (Build your Own Search Service) is Yahoo!'s open search web services platform. The goal of BOSS is simple: to foster innovation in the search industry. Developers, start-ups, and large Internet companies can use BOSS to build and launch web-scale search products that utilize the entire Yahoo! Search index. BOSS gives you access to Yahoo!'s investments in crawling and indexing, ranking and relevancy algorithms, and powerful infrastructure. By combining your unique assets and ideas with our search technology assets, BOSS is a platform for the next generation of search innovation, serving hundreds of millions of users across the Web.
The eXtensible Text Framework (XTF) is a flexible indexing and query tool that supports searching across collections of heterogeneous data and presents results in a highly configurable manner. The highlights of the XTF system are described in an online brochure
WhatToSee
I have a routine problem that sometimes paper titles are not enough to tell me what papers to read in recent conferences, and I often do not have time to read abstracts fully. This collection of scripts is designed to help alleviate the problem. Essentially, what it will do is compare what papers you like to cite with what new papers are citing. High overlap means the paper is probably relevant to you. Sure there are counter-examples, but overall I have found it useful (eg., it has suggested papers to me that are interesting that I would otherwise have missed). Of course, you should also read through titles since that is a somewhat orthogonal source of information.
Here is how to use the system. You upload your personal bibtex file and have the system compare it to a known conference index; it will then present a list of papers, sorted by relevance. If you want to compare to a conference that is not yet indexed, you need to request that indexing take place. This takes about 30 seconds per paper, so you will probably have to be patient.
RaPIDS: Rapid Prototyping of Intuitive Discovery at Stanford
Federated Searching
Federated searching is a strategy for simultaneously searching a number of online resources and pooling the results into one interfiled result set. As part of the RaPIDS (Rapid Prototyping of Intuitive Discovery at Stanford) initiative, SULAIR is experimenting with federated searching as a means of giving scholars a broad view of disparate resources held across many different, isolated systems. For this effort, SULAIR is working with Deep Web Technologies. The company’s federated searching system, Explorit Research Accelerator, is currently powering a number of science, technology and government search portals, including National Digital Library for Agriculture (NDLA), Science.gov, Scitopia, and WorldWideScience.org. SULAIR has developed with Deep Web Technologies three demonstrations of federated searching within the Stanford environment:
Deep Web Technologies redefines the federated search market with its powerful, flexible search solution, Explorit Research Accelerator. Organizations that use Explorit enjoy a custom solution that fits the specific needs of their end users, so searches are not only efficient, they're complete. By combining advanced, real-time search with sophisticated results retrieval, Explorit gives users precise, accurate results delivered with unrivaled agility.
Entrez Programming Utilities are tools that provide access to Entrez data outside of the regular web query interface and may be helpful for retrieving search results for future use in another environment.
Microsoft Live Labs: Accelerating Search in Academic Research 2006 RFP Awards
Microsoft Research announced the twelve recipients of the Microsoft Live Labs: Accelerating Search in Academic Research 2006 RFP awards, totaling $500,000 (USD) in funding. The objective of this RFP is to support Live Labs’ collaboration with the academic research community and is focused on the Internet Search research area. Specifically, this RFP directly addresses the need for more large-scale data by making additional real world search data available to academia. In doing so, Microsoft seeks to further encourage academic research and innovation in search by increasing the availability of relevant, large, and current data sets from MSN Search, new data analysis and algorithm development in Internet Search will be supported.
Book sources
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This page allows users to search for multiple sources for a book given the ISBN number. Spaces and dashes in the ISBN number do not matter. The number starts after the colon for "ISBN-10:" and "ISBN-13:" numbers.
Y. Tan, M. Kan, and D. Lee. JCDL '06: Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries, page 314--315. New York, NY, USA, ACM, (2006)