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The plan of this article is to give an over all brief review on information search strategy. The ten key points mentioned is to indicate procedure of doing Online Literature Search in a scientific methods. The concept of search ta...
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The plan of this article is to give an over all brief review on information search strategy. The ten key points mentioned is to indicate procedure of doing Online Literature Search in a scientific methods. The concept of search tactics describes 29 tactics to be used in information searching. The search tactics are intended to be practically useful in information searching and the approach of searching is designed on online medical databases. It is a basic premise of this article that tactic can make information search more easy and readily applied. The phrase "search strategy" is probably found most often in the literature of on-line searching.
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The problems of (classical) searching and connected searching of weighted trees are known to be computationally hard. In this work we give a polynomial-time 3-approximation algorithm that finds a connected search strategy of a giv...
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The problems of (classical) searching and connected searching of weighted trees are known to be computationally hard. In this work we give a polynomial-time 3-approximation algorithm that finds a connected search strategy of a given weighted tree. This in particular yields constant factor approximation algorithms for the (non-connected) classical searching problems and for the weighted pathwidth problem for this class of graphs.
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Due to the large amount of data storage requirements in computer science now a day, the data must be searched and retrieved in an efficient way. For this, the data can be viewed be organized in a different way or using different d...
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Due to the large amount of data storage requirements in computer science now a day, the data must be searched and retrieved in an efficient way. For this, the data can be viewed be organized in a different way or using different data structures. In this paper a short discussion is given on different searching algorithms and proposed a new simple key search algorithm for interpolation search method. The algorithm that we developed can be referred by the name Expeditious Search Algorithm. It is a simple key searching algorithm which uses divide and conquer technique method. It is a kind of interpolation algorithm. The basic idea of Expeditious Search Algorithm is based on binary search technique. Expeditious Search Algorithm requires the input array in sorted form. The array is divided based on some conditions and any one of the partition is selected for searching the key and all the other sub parts are discarded. This procedure repeats. The algorithm takes the average case time of O(log log n).
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Purpose - The use of search engines has become increasingly common. While Google has an overwhelming majority of the market share, new and innovative search techniques are being developed. An example of these is the clustering int...
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Purpose - The use of search engines has become increasingly common. While Google has an overwhelming majority of the market share, new and innovative search techniques are being developed. An example of these is the clustering interface used by a number of search engines, whereby results are grouped and visualised according to categories. The purpose of this paper is to examine user perceptions and experience of using clustering. Design/methodology/approach - In total, 12 Palmerston North City Library (New Zealand) staff members and patrons were recruited and the data were gathered through both observations of a search using a clustering search engine (Carrot2Clustering) and via semi-structured interviews. The data were analysed according to four themes: features, look and feel, results and clusters. Findings - The findings from this study revealed that the use of clusters can assist users in the search process in several ways. Evidence was also found to support previous research indicating the importance of labelling the clusters. Originality/value - This exploratory research provides some insights into users' perceived cognitive load in using a clustering search engine as compared to using a list-based search engine. The authors explored how searchers compare their overall experience of using clustering search engines to using traditional list-based engines and the extent to which the clustering presentation influences the progression of a search. The authors also examined the extent to which searchers make use of the feedback a clustering search engine provides to refine, rephrase or redefine their initial search.
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While today's web search engines are designed for single-user search, over the years research efforts have shown that complex information needs-which are explorative, open-ended and multi-faceted-can be answered more efficiently a...
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While today's web search engines are designed for single-user search, over the years research efforts have shown that complex information needs-which are explorative, open-ended and multi-faceted-can be answered more efficiently and effectively when searching in collaboration. Collaborative search (and sensemaking) research has investigated techniques, algorithms and interface affordances to gain insights and improve the collaborative search process. It is not hard to imagine that the size of the group collaborating on a search task significantly influences the group's behaviour and search effectiveness. However, a common denominator across almost all existing studies is a fixed group size-usually either pairs, triads or in a few cases four users collaborating. Investigations into larger group sizes and the impact of group size dynamics on users' behaviour and search metrics have so far rarely been considered-and when, then only in a simulation setup. In this work, we investigate in a large-scale user experiment to what extent those simulation results carry over to the real world. To this end, we extended our collaborative search framework SearchX with algorithmic mediation features and ran a large-scale experiment with more than 300 crowd-workers. We consider the collaboration group size as a dependent variable, and investigate collaborations between groups of up to six people. We find that most prior simulation-based results on the impact of collaboration group size on behaviour and search effectiveness cannot be reproduced in our user experiment.
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In this paper we consider the problem of connected edge searching of weighted trees. Barriere et al. claim in [L. Barriere, P. Flocchini, P. Fraigniaud, N. Santoro, Capture of an intruder by mobile agents, in: SPAA'02: Proceedings...
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In this paper we consider the problem of connected edge searching of weighted trees. Barriere et al. claim in [L. Barriere, P. Flocchini, P. Fraigniaud, N. Santoro, Capture of an intruder by mobile agents, in: SPAA'02: Proceedings of the Fourteenth Annual ACM Symposium on Parallel Algorithms and Architectures, ACM, New York, NY, USA, 2002, pp. 200-209] that there exists a polynomial-time algorithm for finding an optimal search strategy, that is, a strategy that minimizes the number of used searchers. However, due to some flaws in their algorithm, the problem turns out to be open. It is proven in this paper that the considered problem is strongly NP-complete even for node-weighted trees (the weight of each edge is 1) with one vertex of degree greater than 2. It is also shown that there exists a polynomial-time algorithm for finding an optimal connected search strategy for a given bounded degree tree with arbitrary weights on the edges and on the vertices. This is an FPT algorithm with respect to the maximum degree of a tree.
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It is widely held that sellers prefer to appear early in a consumer,s search, but evidence suggests this need not be the case. We develop a model which incorporates costly search and costly return and demonstrate that appearing la...
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It is widely held that sellers prefer to appear early in a consumer,s search, but evidence suggests this need not be the case. We develop a model which incorporates costly search and costly return and demonstrate that appearing later may be better. When return is free, prominence is desirable by standard logic, however costly return induces a tradeoff - it benefits an earlier seller by reducing the initial search but also benefits a later seller by preventing return conditional on search. We show that for small search costs later is better whenever high outcomes have a low likelihood, or whenever two independent match value draws are likely to be near one another. Later can still be better if sellers compete in prices prior to search. Finally, with many sellers the optimal position may be first, last, or in between but earlier positions are favored as the number of sellers grows. (C) 2017 Elsevier B.V. All rights reserved.
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O-SNAP is a mobile application that explicitly supports in-person collaborative search by enabling users to physically signal their willingness to share and by facilitating face-to-face search-related communication. The Web extra ...
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O-SNAP is a mobile application that explicitly supports in-person collaborative search by enabling users to physically signal their willingness to share and by facilitating face-to-face search-related communication. The Web extra at http://youtu.be/AKoITuxB9BY is a video in which author Meredith Ringel Morris discusses scenarios that can prompt collaborative information seeking.
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Points out the rate of digital explosion in present era. Defines search engines and thdif types. Mentions various techniques to handle various search engines for getting best results. Highlights the basic features of various indiv...
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Points out the rate of digital explosion in present era. Defines search engines and thdif types. Mentions various techniques to handle various search engines for getting best results. Highlights the basic features of various individual as well as meta seach engines.
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In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using ...
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In retail settings with price promotions, consumers often search across stores and time. However, the search literature typically only models one pass search across stores, ignoring revisits to stores; the choice literature using scanner data has modeled search across time, but not search across stores in the same model. We develop a multipass search model that jointly endogenizes search in both dimensions; our model nests a finite horizon model of search across stores within an infinite horizon model of intertemporal search. We apply our model to milk purchases at grocery stores; hence, the model also accounts for repeat purchases across time, inventory holding by households, and grocery basket effects. We note that the special case without these additional features can be used to study one-time purchases with repeat store visits as in the case of durable goods and online shopping. We formulate the empirical model as a mathematical program with equilibrium constraints and estimate it allowing for latent class heterogeneity using an iterative expectation-maximization algorithm. In contrast to extant research, we find that omitting the temporal dimension underestimates price elasticity. We attribute this difference to the relative frequency of household stockouts and purchase frequency in the milk category. Interestingly, increasing the promotional frequency (while reducing its depth to maintain the mean and variance of prices across all stores) can increase loyalty to the household's preferred store.
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