When merging query results from various information sources or from different search engines, popular methods based on available documents scores or on order ranks in returned lists, its can ensure fast response, but results are often inconsistent. Another approach is downloading contents of top documents for re-indexing and re-ranking to create final ranked result list. This method guarantees better quality but is resource-consuming. In this paper, we compare two methods of merging search results: a) applying formulas to re-evaluate document based on different combinations of returned order ranks, documents titles and snippets; b) Top-Down Re-ranking algorithm (TDR) gradually downloads, calculates scores and adds top documents from each source into the final list. We propose also a new way to re-rank search results based on genetic programming and re-ranking learning. Experimental result shows that the proposed method is better than traditional methods in terms of both quality and time. Povzetek: V prispevkih sta primerjana dva pristopa pri združevanju zadetkov iskanja: z enačbo in z algoritmom TDR, nato pa je primerjana še izvirna metoda.
The study aims at valuing mangrove ecosystem services in Xuan Thuy National Park, Red River Delta, Vietnam. A discrete choice experiment was employed to elicit household willingness to pay (WTP) for a community project to protect mangroves against climate change. A conditional logit model and a random parameter logit model were estimated to identify the relationships between WTP and the different attributes of the mangrove conservation project. The results suggested that local households exhibited strong preferences for mangrove coverage area and storm prevention capacity whereas biodiversity benefits were not greatly perceived by most respondents. High level of heterogeneity in household preferences was found for the high mangrove coverage, and high management level of biodiversity. Furthermore, marginal household WTPs were computed given a change in each attribute level. Hence, the findings will aid in the development of a comprehensive payment for mangrove preservation policy in Vietnam.
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