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This paper introduces a novel ranking refinement approach based on relevance feedback for the task of document retrieval. We focus on the problem of ranking refinement since recent evaluation results from Information Retrieval (IR) systems indicate that current methods are effective retrieving most of the relevant documents for different sets of queries, but they have severe difficulties to generate a pertinent ranking of them. Motivated by these results, we propose a novel method to re-rank the list of documents returned by an IR system. The proposed method is based on a Markov Random Field (MRF) model that classifies the retrieved documents as relevant or irrelevant. The proposed MRF combines: (i) information provided by the base IR system, (ii) similarities among documents in the retrieved list, and (iii) relevance feedback information. Thus, the problem of ranking refinement is reduced to that of minimising an energy function that represents a trade-off between document relevance and inter-document similarity. Experiments were conducted using resources from four different tasks of the Cross Language Evaluation Forum (CLEF) forum as well as from one task of the Text Retrieval Conference (TREC) forum. The obtained results show the feasibility of the method for re-ranking documents in IR and also depict an improvement in mean average precision compared to a state of the art retrieval machine.
Methanol extracts from 24 Trichoderma isolates, selected as biocontrol agents and representating different species and genotypes from three of the four taxonomic sections of this genus (T. sect. Trichoderma, T. sect. Pachybasium and T. sect. Longibrachiatum) were screened for antibacterial, anti-yeast and antifungal activities against a panel of seven bacteria, seven yeasts and six filamentous fungi previously used in similar studies. Two different growth media were tested (potato dextrose broth and CYS80), and all isolates included in the antimicrobial tests showed at least one inhibitory activity against one of the target microorganisms in one of the two culture media. No statistically significant differences were detected in the number of active strains between the two culture media, but the highest number of inhibitory strains against bacteria and fungi were found in strains from Trichoderma sect. Pachybasium, whereas strains from T. sect. Longibrachiatum showed the highest anti-yeast values. In all cases, a correlation was found between the strains that were active against yeasts and fungi. However, some degree of variability was detected for strains within the same taxonomic section. In general terms, strains from T. asperellum (mainly in CYS80 medium), and T. longibrachiatum gave the best non-enzymatic antimicrobial profiles.
Genetic variability within 69 biocontrol isolates of Trichoderma, obtained from different geographical locations and culture collections and selected as biocontrol agents, was studied. Sequence data, obtained from the ITS1 region of rDNA and a fragment of the translation elongation factor 1 (tef1) gene, were used in a phylogenetic analysis. Phylograms showing similar topologies were generated using alignments containing the ITS1 region or a portion of the tef1 gene. 21 distinct ITS1 sequence types and 17 distinct tef1 sequence types were identified among the 69 isolates. More than 50% of the potential biocontrol strains were grouped within Trichoderma sect. Pachybasium; of these, 81% were grouped within the cluster that included the ex-type strains of T. harzianum and T. inhamatum, and 16% were grouped with T. virens. Within T. sect. Trichoderma, which included 36% of the 69 strains, 56% were grouped with T. asperellum, and 24% with T. viride, T. atroviride or T. koningii. Only 10% of the strains studied were located in T. sect. Longibrachiatum.
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