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Knowledge retrieval

Knowledge retrieval
Knowledge Retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology (theory of knowledge), cognitive psychology, cognitive neuroscience, logic and inference, machine learning and knowledge discovery, linguistics, and information technology. Overview[edit] In the field of retrieval systems, established approaches include: Data Retrieval Systems (DRS), such as database management systems, are well suitable for the storage and retrieval of structured data.Information Retrieval Systems (IRS), such as web search engines, are very effective in finding the relevant documents or web pages. Both approaches require a user to read and analyze often long lists of data sets or documents in order to extract meaning. The goal of knowledge retrieval systems is to reduce the burden of those processes by improved search and representation. References[edit] Related:  Curate Content Research

Metaknowledge Metaknowledge or meta-knowledge is knowledge about a preselected knowledge. For the reason of different definitions of knowledge in the subject matter literature, meta-information is or is not included in meta-knowledge. Detailed cognitive, systemic and epistemic study of human knowledge requires a distinguishing of these concepts. but in the common language knowledge includes information, and, for example, bibliographic data are considered as a meta-knowledge. Metaknowledge may be automatically harvested from electronic publication archives, to reveal patterns in research, relationships between researchers and institutions and to identify contradictory results.[2] See also[edit] References[edit] External links[edit]

Knowledge extraction Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL (data warehouse), the main criteria is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data. Overview[edit] After the standardization of knowledge representation languages such as RDF and OWL, much research has been conducted in the area, especially regarding transforming relational databases into RDF, identity resolution, knowledge discovery and ontology learning. Examples[edit] XML[edit]

Hermeneutics Hermes, messenger of the gods. Hermeneutics /hɜrməˈnjuːtɪks/ is the theory of text interpretation, especially the interpretation of biblical texts, wisdom literature, and philosophical texts.[1][2] The terms "hermeneutics" and "exegesis" are sometimes used interchangeably. Hermeneutics is a wider discipline that includes written, verbal, and nonverbal communication. Exegesis focuses primarily upon texts. Hermeneutic, as a singular noun, refers to a single particular method or strand of interpretation (see, in contrast, double hermeneutic). Hermeneutics initially applied to the interpretation, or exegesis, of scripture. Etymology[edit] Hermeneutics is derived from the Greek word ἑρμηνεύω (hermeneuō, 'translate' or 'interpret').[6] It was introduced into philosophy mainly through the title of Aristotle's work On Interpretation, commonly referred to by its Latin title De Interpretatione. Folk etymology[edit] Aristotle and Plato[edit] The meaning of the poem thus becomes open to ridicule.

What’s the law around aggregating news online? A Harvard Law report on the risks and the best practices [So much of the web is built around aggregation — gathering together interesting and useful things from around the Internet and presenting them in new ways to an audience. It’s the foundation of blogging and social media. But it’s also the subject of much legal debate, particularly among the news organizations whose material is often what’s being gathered and presented. Kimberley Isbell of our friends the Citizen Media Law Project has assembled a terrific white paper on the current state of the law surrounding aggregation — what courts have approved, what they haven’t, and where the (many) grey areas still remain. This should be required reading for anyone interested in where aggregation and linking are headed. You can get the full version of the paper (with footnotes) here; I’ve added some links for context. During the past decade, the Internet has become an important news source for most Americans. What is a news aggregator? Can they do that? AFP v. Associated Press v. So is it legal?

Concordancer Concordancers are also used in corpus linguistics to retrieve alphabetically or otherwise sorted lists of linguistic data from the corpus in question, which the corpus linguist then analyzes. Concordancers used in corpus linguistics[edit] AntConc (freeware)ApSIC XbenchMonoConcPowerConc (freeware)WordSmithSketch EngineNoSketch Engine (open source)GlossaNet/Unitex (open-source free software),AdTAT(free software developed by The University of Adelaide)CorpusEyeKH Coder (open-source free software),myCAT from Olanto (open-source)Linguistic Toolbox (freeware).[1][2] See also[edit] References[edit] External links[edit] Museums and the Web 2010: Papers: Miller, E. and D. Wood, Recollection: Building Communities for Distributed Curation and Data Sharing Background The National Digital Information Infrastructure and Preservation Program at the Library of Congress is an initiative to develop a national strategy to collect, archive and preserve the burgeoning amounts of digital content for current and future generations. It is based on an understanding that digital stewardship on a national scale depends on active cooperation between communities. These diverse collections are held in the dispersed repositories and archival systems of over 130 partner institutions where each organization collects, manages, and stores at-risk digital content according to what is most suitable for the industry or domain that it serves. NDIIPP partners understand through experience that aggregating and sharing diverse collections is very challenging. Early in 2009, a pilot project recognizing the specific characteristics of this community was initiated by the Library of Congress and Zepheira. Specific goals for the Recollection project are to: How It Works

Concordance (publishing) Mordecai Nathan's Hebrew-Latin Concordance of the Bible A concordance is more than an index; additional material, such as commentary, definitions, and topical cross-indexing make producing them a labor-intensive process, even when assisted by computers. Although an automatically generated index lacks the richness of a published concordance, the ability to combine the result of queries concerning multiple terms (such as searching for words near other words) has reduced interest in concordance publishing. In addition, mathematical technices such as Latent Semantic Indexing have been proposed as a means of automatically identifying linguistic information based on word context. A bilingual concordance is a concordance based on aligned parallel text. A topical concordance is a list of subjects that a book (usually The Bible) covers, with the immediate context of the coverage of those subjects. Concordances are frequently used in linguistics, when studying a text.

Real-Time News Curation - The Complete Guide Part 4: Process, Key Tasks, Workflow I have received a lot of emails from readers asking to illustrate more clearly what the actual typical tasks of a news curator are, and what are the tools that someone would need to use to carry them out. In Part 4 and 5 of this guide I am looking specifically at both the workflow, the tasks involved as well as at the attributes, qualities and skills that a newsmaster, or real-time news curator should have. 1. Sequence your selected news stories to provide the most valuable information reading experience to your readers. There are likely more tasks and elements to the news curator workflow that I have been able to identify right here. Please feel free to suggest in the comment area, what you think should be added to this set of tasks. Photo credits:1.

Content analysis Content analysis is "a wide and heterogeneous set of manual or computer-assisted techniques for contextualized interpretations of documents produced by communication processes in the strict sense of that phrase (any kind of text, written, iconic, multimedia, etc.) or signification processes (traces and artifacts), having as ultimate goal the production of valid and trustworthy inferences."[1] On the other side, Content Analysis can also study traces (documents from past times) and artifacts (non-linguistic documents), which come from communication processes in a broad sense of that phrase - commonly referred to as "signification" in Semiotics (in the absence of an intentional sender, semiosis is developed by abduction).[1] Over the years, content analysis has been applied to a variety of scopes. In recent times, particularly with the advent of mass communication, content analysis has known an increasing use to deeply analyse and understand media content and media logic. Description[edit]

The Accidental Taxonomist: Taxonomy Trends and Future What are the trends in taxonomies, and where is the field going? The future of taxonomies turned out to be a unifying theme of last week’s annual Taxonomy Boot Camp conference, in Washington, DC, the premier event in taxonomies, from its opening keynote to its closing panel. “From Cataloguer to Designer” was the title of the opening keynote, an excellent presentation by consultant Patrick Lambe of Straits Knowledge. He said that there are new opportunities for taxonomists, especially in the technology space, if they change their mindset and their role from that of cataloguers, who describe the world as it is, to that of designers, who plan things as they could be. New trends involving taxonomies that he described include search-based applications, autoclassification, and knowledge graphs (such as the automatically curated index card of key information on a topic, as appears in some Google search results). New trends and technologies were discussed in individual presentations, too.

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