Harter, S.P. (1986). Online Information retrieval. Orlando: Academic Press.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....based on the notion of elementary queries (EQ) Harter used a single search topic to illustrate how the method could be applied. He designed a high recall oriented query plan (see Fig 1) Harter applied the building block search strategy which quite commonly used by professional searchers [6, 9, 12, 16]. The major steps of the building blocks strategy are 1) Identify major facets and their logical relationships with one another. 2) Identify query terms that represent each facet: words, phrases, etc. 3) Combine the query terms of a facet by disjunction (OR operation) 4) Combine the facets by ....

....are 1) Identify major facets and their logical relationships with one another. 2) Identify query terms that represent each facet: words, phrases, etc. 3) Combine the query terms of a facet by disjunction (OR operation) 4) Combine the facets by conjunction or negation (AND or ANDNOT operation) [9]. The notion of facet is important in query planning. It is a concept that is identified from, and defines one exclusive aspect of a search topic. In step 2, a typical goal is to discover all plausible query terms appropriate in representing the selected facet. Next, Harter retrieved all ....

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Harter, S.P. (1986). Online Information retrieval. Orlando: Academic Press.

....themselves are connected by conjunctions. The facets of a request are difficult to identify plausibly in a general operational context by automatic means. On the other hand, the identification and selection of query facets is a routine query planning task for a professional searcher, see e.g. [25, 26, 27]. Query facets are quite consistently identified by experienced searchers assuming that a textual information need Journal of Documentation, vol. 57, no. 3, May 2001, pp. 358 374 6 description is available [12, 28] The test collection used here provides inclusive query plans designed by an ....

Harter, S.P.Online Information retrieval. Orlando: Academic Press, 1986.

....One of its goals is to support the user performing effective tasks. 5 2.2 Information retrieval models. A general view of an information retrieval system is that the IR system consists of a device interposed between a potential user of information and the information collection itself (Harter, 1986, p. 2) Generally, an IR system has three major components: the databasewhich consists of the content and the physical container; the communication channel or interface between the user and the database, which has a physical component that facilitates interaction, and a conceptual component that ....

Harter, S. (1986), Online information retrieval. Concepts, principles, and techniques.

.... of iteration, that part of a search bounded by uses of the Run Query button (first iteration beginning with starting the search, last ending with saving the final query) is equivalent to the concept of cycle as used in discussing interaction in traditional boolean retrieval systems (cf. Harter1986] The mean number of iterations per search, for all searchers, was 7.760. There was no significant difference in number of iterations by searchers, but the number of iterations increased significantly by trial (that is, by hardness) F (4; 36) 4:607; p :01 (see table 13) There was a medium ....

Harter, S. P. (1986). Online Information Retrieval. San Diego, CA, Academic Press.

....of word frequency counts. A common feature of all these representations, however, is that they ignore the ordering of words in a document; instead a documents is treated as an unordered bag of words . However, many modern information retrieval systems support queries that exploit word ordering [ Harter, 1986, pages 81 94 ] It seems reasonable to conjecture that adopting a representation that includes ordering information might improve learning performance. One way to represent ordering information directly is with logic. Labeled examples of the target class C can be represented as labeled ground ....

Stepher P. Harter. Online Information Retrieval. Academic Press, San Diego, 1986.

....2 ) is true when jp 1 Gamma p 2 j 1. ffl near2 (p 1 ; p 2 ) is true when jp 1 Gamma p 2 j 2. ffl near3 (p 1 ; p 2 ) is true when jp 1 Gamma p 2 j 3. ffl after(p 1 ; p 2 ) is true when p 2 p 1 . Many modern IR systems support queries using the non word relations succ, after, and neark [ Harter, 1986, pages 81 94 ] In our experiments, the non word Figure 1: FOIL s representation for the example dataset Examples and word facts: mlsession(d1) improving(d1,1) efficiency(d1,2) by(d1,3) learning(d1,4) mlsession(d2) learning(d2,1) dnf(d2,2) by(d2,3) decision(d2,4) trees(d2,5) ....

Stepher P. Harter. Online Information Retrieval. Academic Press, San Diego, 1986.

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Harter, S.P. (1986). Online Information retrieval. Orlando: Academic Press.

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Harter, Stephen P. 1986. Online information retrieval. Academic Press, Inc., Orlando, Florida.

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