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Diigo Launches – More Than Just Bookmarking
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es, gather sources, and easily publish a post to your blog, Diigo may be your solution. Diigo allows you to add multiple blogs to your account, verify them, and easily publish a post, however you may only publish and cannot manage old entries. What I like is that while you browse the web and you come across a site talking about a specific topic you want to expand on, you can right click and select, “Blog This,” which will then direct you to the blogging area where you can write your post along with that site being your source. The other method is by simply going to your bookmarks section and selecting a bookmark, or multiple bookm
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Data mining – Wikipedia, the free encyclopedia
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Data mining
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Data mining is the process of extracting hidden patterns from large amounts of data
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The term data mining has also been used in a related but negative sense, to mean the deliberate searching for apparent but not necessarily representative patterns in large amounts of data. To avoid confusion with the other sense, the terms data dredging and data snooping are often used. Note, however, that dredging and snooping can be (and sometimes are) used as exploratory tools when developing and clarifying hypotheses.
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Comparison of Web-scraping software – Wikipedia, the free encyclopedia
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The following companies can scrape websites for you into desired output formats.
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The following companies can scrape websites for you into desired output formats.
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The following companies can scrape websites for you into desired output formats.
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Developer’s Guide: Protocol and Java – Google Notebook Data API – Google Code
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Developer’s Guide: Protocol and Java
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Developer’s Guide: Protocol and Java
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The Google Notebook Data API allows client applications to view public notebook content in the form of Google Data API feeds. Your client application can request a list of notes from a public notebook, request a list of public notebooks owned by a particular user, and query for notes that match particular criteria.
Google Notebook feeds are currently read-only and public-only; you can’t send data to Notebook using the Data API, and you can’t get a feed of private Notebook data
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ACCELERATING DISCOVERY AND INNOVATION BY BRIDGING UNCONNECTED DISCIPLINES
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DEVELOPMENT OF QUERIES FOR INFORMATION RETRIEVAL
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The key problem with most standard search approaches is that the analyst is required to hypothesize the search terms in the context of the application, rather than use the database to provide the search terms appropriate to the context in which they are actually imbedded
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For general language databases, automated text retrieval using linguistic rules and supporting on-line dictionaries could provide marginally acceptable results for some classes of users.
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For highly technical S&T databases, the focus of the text retrieval techniques discussed in the present Appendix, automated text retrieval results in poor retrieval performance.
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Natural language processors have severe limitations when applied to highly specialized technical terms.
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yield the search terms from the language and context of the authors
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Typical R&D literature surveys have none of these three quality conditions.
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When applied to the literature in a technical field, co-word analysis allows a map of the relationship among technical themes to be constructed.
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Term Co-occurrence in information retrieval can be used to expand on an initial query,
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These additional terms could also be used to remove irrelevant documents.
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Query Expansion provided the greatest improvement in performance when the original query gave reasonable retrieval results
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The main idea consists of choosing important terms, or expressions, attached to certain previously retrieved documents that have been identified as relevant by the users, and of enhancing the importance of these terms in a new query formulation
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Relevance Feedback
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Performance with feedback improved substantially over the no feedback case.
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Results show that terms selected from particular database fields of retrieved items during term relevance feedback (TRF) were more effective than search terms from the intermediary, database thesauri or users’ domain knowledge during the interaction.
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Classical co-word analysis applied to index/ key words for the purpose of science and technology (S&T) evaluation does not allow the richness of the semantic relationships in full text to be exploited, and it is restricted to formally published papers
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In order to allow any form of free text to be used, Database Tomography (DT) was developed.
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The first step is identification of the main themes of the text being analyzed. The second step is determination of the quantitative and qualitative relationships among the main themes and their secondary themes.
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The highest frequency technical content phrases are selected by topical experts as the pervasive themes of the full database.
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Second, for each theme phrase, the frequencies of phrases within some domain centered about the theme phrase are computed for every occurrence of the theme phrase in the full text, and a phrase frequency dictionary is constructed.
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This phrase frequency dictionary contains the phrases closely related to the theme phrase.
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Both quantitative and qualitative analyses are performed by the topical expert for each dictionary (hereafter called cluster) yielding, among many results, those sub-themes closely related to and supportive of the main cluster theme.
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Third, threshold values are assigned
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these indices are used to filter out the phrases most closely related to the cluster theme
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the qualitative analyses of the extracted data by the topical experts have been at least as important as the quantitative analyses.
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a variety of different analyses can be performed.
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the final results have been identification of the pervasive technical themes of the database, the relationship among these themes, and the relationship of supporting sub-thrust areas (both high and low frequency)
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Expert-centric S&T text mining provides an in-depth understanding/ identification of the technical concepts and their inter-relationships, whereas the computer-centric approach focused on the more superficial level of context-free phrases.
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Simulated Nucleation
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a small core group of documents mainly relevant to the topic of interest is identified
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An inherent assumption is then made that the bibliometric and phrase patterns and phrase combinations characteristic of this relevant core group would be found to occur in other relevant documents. Therefore, these bibliometric and phrase patterns and phrase combinations can be used to expand the search query,
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using computer-based clustering techniques for separating the relevant from non-relevant records (e.g., see Hearst (1996) and Zamir (1999) for examples of clustering approaches to separate relevant from non-relevant documents)
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Kostoff et al, 2005a
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IV-A. Overview of Updated Process
The operational objective of Simulated Nucleation is to generate a query that will have the following characteristics:
*Retrieve the maximum number of records in the technical discipline of interest
*Retrieve substantial numbers of records in closely allied disciplines
*Retrieve substantial numbers of records in disparate disciplines that have some connection to the technical discipline of interest
*Retrieve records in aggregate with high signal-to-noise ratio (number of desirable records large compared to number of undesirable records)
*Retrieve records with high marginal utility (each additional query term will retrieve large ratio of desirable to undesirable records)
*Minimize query size to conform to limit requirements of search engine(s) used
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To achieve these objectives, the Simulated Nucleation process has been improved and updated, and now contains the following steps:
*Definition of study scope
*Generation of query development strategy
*Generation of test query
*Retrieve records from database; select sample
*Divide sample records into relevant and non-relevant categories
*Perform computational linguistics on each category
*Use new algorithms to identify phrases unique to each category
*Use new algorithms to identify phrase combinations unique to each category
*Use new algorithms to identify marginal value of adding each phrase and phrase combination to query
*Construct modified query
*Repeat process until convergence obtained
Each of these steps will now be described in more detail, and the upgrades and improvements will be emphasized.
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in general, a separate query had to be developed for each database examined
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Relation of Query Structure to Database Fields Selected
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Relation of Query Structure to Expert(s) Perspectives
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there is no evidence that a rigorous query of high quality and utility (comparable to those developed using Simulated Nucleation and the semi-structured textual SCI and EC databases) could be made of the highly unstructured Web as it exists now and in the foreseeable future.
- better for science and tech databases – post by ippisl
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Generic Term Initialization
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While the emphasis of these later iterations was reduction of non-relevant records
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Specific Term Initialization
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Because of the specificity of the query terms, records relating to the more general theme and scope of the study may be overlooked.
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having to make a binary decision (on the relevance or non-relevance of a retrieved record) sharpens the focus of the study measurably.
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DT has focused on two types of congruency metric patterns for identifying candidate query modification terms: phrase frequencies and phrase proximity statistics
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and then the phrases in close proximity to selected theme phrases in the Abstracts were also obtained with the DT algorithms.
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Introduction to Diigo Toolbar. Diigo Toolbar installed.
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Diigo Toolbar is now installed on your browser
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Diigo Toolbar is now installed on your browser
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Diigo Toolbar is now installed on your browser
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how do I build web pages people can annotate | Ask Metafilter
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what you wan
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you want
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ing our text version of this document.May 24, 2002 … The Data W
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Amazon.com: Made to Stick: Why Some Ideas Survive and Others Die: Chip Heath, Dan Heath: Books
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With an entertaining blend of case studies and startling research, the Heath brothers lay out the critical elements of a sticky idea. They are–
1. Simplicity
2. Unexpectedness
3. Concreteness
4. Credibility
5. Emotions
6. Stories
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Ask your audience a question 
They answer using SMS text messages or the web (try voting!) 
Results update live in your web browser or PowerPoint -
Poll Everywhere
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creative places to use Poll Everywhere:
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Amazon Introduces Upgraded Kindle Book Reader – NYTimes.com
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Amazon.com on Monday introduced the Kindle 2
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The announcement strengthens the bid by Amazon for control of the e-book market
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most significantly, Amazon said it would start selling e-books that can be read on mobile phones and other devices
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several incremental improvements
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The Kindle 2 has
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new feature, Whispersync, which would allow readers to begin a book on one Kindle and continue, at the same point in the text, on another Kindle or a mobile phone.
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Google said last week that it would soon sell books from its publishing partners for reading on mobile devices
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Addressing Google’s initiatives, Mr. Bezos said in an interview that Amazon knows what book buyers want and stressed the company’s digital catalog of 230,000 newer books and best sellers.
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Apple poses another potential threat to Amazon’s plans.
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But some worry that Amazon may be assuming too much control over pricing
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Amazon generally charges $9.99 for the digital versions of best sellers
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That means that for now, Amazon is taking a loss or making a small margin on the sale of some e-books.
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Mr. Bezos disagreed. “E-books should be cheaper than physical books.
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“The thought that there might be one very dominant player who could squeeze most of the profits out of this new market is frightening for authors and publishers,” Mr. Aiken said.
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publishers have remained vigilant in fostering competition in the e-book market.
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Easy Website Highlighting and Notes with Awesome Highlighter
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s interesting. Will give it a try. I find bookmarking sites an easy affair these days with both Opera and Firefox doing a great job of syncing all the bookmarks online so they are always available no matter what.
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Sep 2007 12:41 PM CDT
MIT OpenCourseWare | Sloan School of Management | 15.062 Data Mining, Spring 2003 | Home
Posted: 28 Sep 2007 12:40 PM CDT
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WORKS OF SAKIR KOCABAS: Elements of Scientific Research and Discovery
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Elements of Scientific Research and Discovery >
ELEMENTS OF SCIENTIFIC RESEARCH AND DISCOVERY: >
A Study with CER in High-Temperature Superconductivity >Sakir Kocabas >
Dept. of Space Engineering, Istanbul Technical University, >
Maslak 80626, Istanbul, Turkey. >Abstract >
In this paper we describe a program, CER, which models some of the research activities carried out in the process of the discovery of high-temperature superconductors in 1986 and 1987. These activities include goal and strategy choosing, literature searches, proposing experiments, expectation setting, designing and conducting experiments, data collection, generating and testing hypotheses, modifying hypotheses, and generating explanations. >
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Elements of Scientific Research and Discovery
ELEMENTS OF SCIENTIFIC RESEARCH AND DISCOVERY:
A Study with CER in High-Temperature SuperconductivitySakir Kocabas
Dept. of Space Engineering, Istanbul Technical University,
Maslak 80626, Istanbul, Turkey.Abstract
In this paper we describe a program, CER, which models some of the research activities carried out in the process of the discovery of high-temperature superconductors in 1986 and 1987. These activities include goal and strategy choosing, literature searches, proposing experiments, expectation setting, designing and conducting experiments, data collection, generating and testing hypotheses, modifying hypotheses, and generating explanations.
CER’s design includes many of the elements of scientific research and discovery and provides a step toward a complete computational model. The system has 17 discovery operators which use over 150 methodological rules many of which are general and applicable to other domains of physics and chemistry.
Keywords: Scientific discovery, autonomous operators, methodological rules, consistency, completeness, hypothesis generation, scientific explanation.
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Glassy Eyes | Eyeglasses. Good eyeglasses. Cheap.
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A YEAR) eyeglasses after finding your site.
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sitting_duck_1.jpg (תמונת JPEG, 257×322 פיקסלים)
- – post by ippisl
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to MIT. As they start doing research with their professors, as many MIT undergraduates do, they learn another healthy lesson, namely, a professor may well behave like a fumbling idiot.
The drive for excellence and
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human body
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human body
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Home clinic programme: an alternative model for pr…[Int J Ment Health Nurs. 2006] – PubMed Result
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ffering the opportunity for
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Nurse-led general practice: the changing face of general practice?
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Nurse-led general practice: the changing face of general practice?
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Posted from Diigo. The rest of my favorite links are here.
