It's all about the context

A Context is a collection of data, often stored in a Map or in a custom class which acts as a struct with accessors and modifiers.

It is used for maintaining state and for sharing information within a system.

See this PDF for an indepth description.

Though it can be used for efficient and effective data sharing, you should note that many are wary of the Context pattern as an anti-pattern.

- See the journal French Metablog with today different posts - Jean-Philippe Pastor

Unexpected relationships with a machine

An immediate goal of text data mining is to construct synopses of the hypertextual material: summaries of the topics which are covered by the texts in data base according to criteria defined by the scriptor.

Another goal is to identify salient points: concise lists of different topics, if possible in order of importance, adjustable in depth.An important goal is also taxonomy (keywords in the data base): determination of the topics in the documents which are (or should be) of interest to the reader.

This is to be followed by classification: the grouping of documents containing different topics, either as defined by the scriptor, or as defined by the information content. The most valuable help for the hypertextual reader consists of the identification of dependencies of the different topics on each other, especially of unexpected relationships.

Download ebooks on http://www.frenchtheory.com/ - See that post with different algorithms in metabole - See the journal French Metablog with today different posts -

PHONEREADER Library - - Jean-Philippe Pastor

Information retrieval

Information retrieval (IR) is the science of searching for information in documents, searching for documents themselves, searching for metadata which describe documents, or searching within databases, whether relational stand-alone databases or hypertextually-networked databases such as the World Wide Web. There is a common confusion, however, between data retrieval, document retrieval, information retrieval, and text retrieval, and each of these has its own bodies of literature, theory, praxis and technologies. IR is interdisciplinary, based on computer science, mathematics, library science, information science, information architecture, cognitive psychology, linguistics, statistics and physics.
Automated IR systems are used to reduce information overload. Many universities and public libraries use IR systems to provide access to books, journals, and other documents. Web search engines such as Google, Yahoo search and Live Search (formerly MSN Search) are the most visible IR applications.

Download ebooks on http://www.frenchtheory.com/ - See that post with different algorithms in metabole - See the journal French Metablog with today different posts -

Absolute Mining

Hegel defines the Absolute Idea as the “unity of the Theoretical Idea and the Practical Idea".

The Theoretical Idea is the completed Notion or concrete concept of the world or object; the Practical Idea is the activity expressing this concept (practice); the unity of the two means fully “conscious practice”, people acting in true accord with their own nature.

Download ebooks on http://www.frenchtheory.com/

See that post with different algorithms in metabole

See the journal French Metablog with today different posts

Reality Mining

Reality mining explores a huge dataset on individual & group human behavior by capturing communication, proximity, location, & activity information from 100 subjects at MIT.

Several different interactive visualizations have been implemented to represent this huge, time-based dataset (approximately 350,000 hours or ~40 years of continious data on call logs, bluetooth devices in proximity, cell tower IDs, application usage, & phone status such as charging/idle).

So where's the value here? Taking the high road, MIT researchers say that you can use this sort of data to understand how organizational dynamics happen at work. You could streamline workflows and improve interoffice dynamics. As one example of reality mining, the Red Sox won the pennant during the study -- and the smartphones noted that it threw all the participants' behaviors into a tizzy. That reminds me of back during the first gulf war--Desert Storm--news outlets discovered that whenever Pentagon staffers stayed late and ordered lots of delivery pizza, something big was about to happen in the Middle East. So it sounds like we can think of Reality Mining as an automated way to collect intelligence about our lives through tell-tale signs like phone calls to pizza delivery restaurants.

Download ebooks on http://www.frenchtheory.com/

See that post with different algorithms in metabole

See the journal French Metablog with today different posts

Data mining and hypertextual material

An immediate goal of text data mining is to construct synopses of the hypertextual material: summaries of the topics which are covered by the texts in data base according to criteria defined by the scriptor.

Another goal is to identify salient points: concise lists of different topics, if possible in order of importance, adjustable in depth.An important goal is also taxonomy (keywords in the data base): determination of the topics in the documents which are (or should be) of interest to the reader. This is to be followed by classification: the grouping of documents containing different topics, either as defined by the scriptor, or as defined by the information content.

The most valuable help for the hypertextual reader consists of the identification of dependencies of the different topics on each other, especially of unexpected relationships.

Download ebooks on http://www.frenchtheory.com/
See that post with different algorithms in metabole
See the journal French Metablog with today different posts

Web services

The old perception is that closed data is a competitive advantage.

The new reality is that open data is a competitive advantage. The likely solution then is to stop worrying about protecting information and instead start charging for it, by offering an API. Having a small fee per API call (think Amazon Web Services) is likely to be acceptable, since the cost for any given subscriber of the service is not going to be high. But there is a big opportunity to make money on volume. This is what Amazon is betting on with their Web Services strategy and it is probably a good bet.

Download ebooks on http://www.frenchtheory.com/
See that post with different algorithms in metabole
See the journal French Metablog with today different posts