By Yacine Laalaoui, Nizar Bouguila
This ebook provides numerous fresh functions of synthetic Intelligence in details and conversation applied sciences akin to seek and Optimization equipment, computing device studying, info illustration and Ontologies, and Multi-agent platforms. the most goal of this booklet is to aid details and conversation applied sciences (ICT) practitioners in handling successfully their systems utilizing AI instruments and strategies and to supply them with enough man made Intelligence history to house real-life difficulties.
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Extra resources for Artificial Intelligence Applications in Information and Communication Technologies
Kechid 6 The Overall Algorithm The ACO algorithms are used to search the sub-collections determined by the inverted file. The overall ant system algorithm called GAS-IR follows the classical schema of information retrieval process and can be outlined in Algorithm 5. Algorithm 5 GAS-IR Input: IF: Inverted File; Q: Query; Output: best: a document that is the most similar with Q; 1: best = a document drawn at random; 2: for each term t of Q do 3: Nt = I F(t); the subcollection of Inverted File of term t 4: let d be the document returned by AS-IR(); 5: if f (d) > f (best) then best = d ; 6: end if 7: end for This way, only the documents that share at least one term with the query are searched and this leads to optimize the runtime.
From this point of view, it is more reasonable to measure the avg. runtime of the default scheduling policy, which is used to create the initial schedule after each new job arrival. In our solution it is the Conservative backfilling with the linear schedule compression (CONS-L), as discussed in Sect. 1. Otherwise, CONS-L is not included in other experiments, as it is a weaker version of CONS policy with a weaker performance and fairness results. Its application makes sense only if accompanied by further RS optimization.
Besides, the query is modelled exactly as a document. The weight of a term in a document is computed using the expression t f ∗ id f where tf represents the term frequency in the document and idf is the inverted frequency computed usually as follows: 34 Y. Drias and S. Kechid id f = log( m ) df where m represents the total number of documents and df is the number of documents that contain the term. The component tf indicates the importance of the term for the document, while idf expresses the power of discrimination of this term in the whole document collection.
Artificial Intelligence Applications in Information and Communication Technologies by Yacine Laalaoui, Nizar Bouguila