Distributed Agents to Retrieve Web Intelligence
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Extended Search

Document procurement

From Search Engine database documents are "pumped out" as a function of how they are tagged, adjusted to standards. A Logical Tree of a given Major Subject (discipline) is depicted. When queried by a pair [k, s] well ranked documents are even highly focused by k. Once optimized by preferences outcome (red dot) is carried to i-Website.

Procurement Shells
See How to Explore the Whole Web

Darwin-FIRST delivers to you its Extended II content database for the discipline of your choice. It reaches nearly 500,000 documents for each discipline retrieved from a pool of pre selected Search Engines. This database is updated quarterly. The pool is queried and processed for the same pair (k, s) of your actual query by a special procurebot_ks agent but its outcome is optimized as a function of its subject' pair along four steps.

By extended search (See How Extended Search Works) we mean an "optimized" conventional search. Darwin-FIRST content searching strategy is based on pairs (k, s) instead of k alone. This "searching second dimension" assures a fast searching convergence in ratios that goes as high as 1,000:1 and at the same time presence of authorities in the Top Lists. Of course subjects must be precisely expressed and belong to world renowned Major Subjects' Logical Trees. For instance in our ICT Map we use as s-dimension a merge of the two world renowned curricula: the ACM 2001 Curricula and UNESCO-IFIP Information and Computing Curricula. As long as pairs (k, s) make reference to any of these two Curricula the chance of authorities on Top Lists of major Search Engines is assured as we have explained in our White Papers.

To optimize the search FIRST "retrievebot" agents are customized and tuned-up for each Major Subject taking into account the following set of preferences and priorities:

Word preferences: Chief Editor determines Bad Words and Good Words sets within URL's descriptions. Examples of Good Words are: [faq, guide, facilitator, manual, tutorial, essay, research]; examples of Bad Words are: [book, e-book, course, conference, symposium, workshop, seminar, syllabus], and many others use to "sell" courses, books, or to announce courses, conferences, seminars, workshops.

Domain Preferences: Chief Editor determines priorities, like for instance, edu => org => net => gov => mil => com.

Super Authorities Paths: For some subjects Chief Editor is enabled to assign higher priorities to certain paths. The reverse could also be done.

Suffixes and prefixes preferences: Chief Editor is enabled to "train" agents to avoid/prefer certain suffixes or prefixes, for instance co instead of com o vice versa, certain country domains, etc.

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