Artículos de revistas: "Diversity search"

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Ishiguro, Shingo. "Contracts, search, and organizational diversity". European Economic Review 54, n.º 5 (julio de 2010): 678–91. http://dx.doi.org/10.1016/j.euroecorev.2009.12.002.

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Linhares, Alexandre y Horacio Hideki Yanasse. "Search intensity versus search diversity: a false trade off?" Applied Intelligence 32, n.º 3 (13 de septiembre de 2008): 279–91. http://dx.doi.org/10.1007/s10489-008-0145-8.

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Muralidhara, Koteshwara. "In Search of Unity in Diversity". Indian Journal of Endocrinology and Metabolism 26, n.º 2 (2022): 191. http://dx.doi.org/10.4103/ijem.ijem_74_22.

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Raman, Karthik, Paul N. Bennett y Kevyn Collins-Thompson. "Understanding Intrinsic Diversity in Web Search". ACM Transactions on Information Systems 32, n.º 4 (28 de octubre de 2014): 1–45. http://dx.doi.org/10.1145/2629553.

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5

Meighan, Clement W. "Letters: In Search of Intellectual Diversity". Academe 80, n.º 5 (1994): 3. http://dx.doi.org/10.2307/40250654.

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Krestel, Ralf y Peter Fankhauser. "Reranking web search results for diversity". Information Retrieval 15, n.º 5 (1 de diciembre de 2011): 458–77. http://dx.doi.org/10.1007/s10791-011-9179-3.

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7

Bendl, Regine, Alexander Fleischmann y Angelika Schmidt. "In Search for Diversity in Alternative Organizations". Academy of Management Proceedings 2018, n.º 1 (agosto de 2018): 17134. http://dx.doi.org/10.5465/ambpp.2018.17134abstract.

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8

Yom-Tov, Elad, Susan Dumais y Qi Guo. "Promoting Civil Discourse Through Search Engine Diversity". Social Science Computer Review 32, n.º 2 (27 de noviembre de 2013): 145–54. http://dx.doi.org/10.1177/0894439313506838.

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9

Ghansah, Benjamin y Shengli Wu. "A Mean-Variance Analysis Based Approach for Search Result Diversification in Federated Search". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, n.º 02 (abril de 2016): 195–211. http://dx.doi.org/10.1142/s0218488516500100.

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Resource Selection is an important step in a federated search environment. The goal of this work was to improve the collection selection process by selecting collections in terms of relevance and diversity, to best answer a user's query. Sampled documents from the Central Sample Database are first ranked by Indri retrieval algorithm and later re-ranked by a Mean-Standard deviation method that reduces uncertainty and improves diversity of collection sources. A comparative evaluation with the R-based diversification metrics shows that the proposed method significantly outperforms the baseline diversification methods; ReDDE+MMR, ReDDE+MAP-IA and state-of-the-art resource selection methods (ReDDE and CORI) in all metrics.

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10

Messeni Petruzzelli, Antonio y Daniele Rotolo. "Institutional diversity, internal search behaviour, and joint-innovations". Management Decision 53, n.º 9 (19 de octubre de 2015): 2088–106. http://dx.doi.org/10.1108/md-05-2014-0256.

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Purpose – The purpose of this paper is to investigate the innovation performance of R & D collaborations from an institutional perspective. Design/methodology/approach – The authors conduct an empirical analysis based on 487 joint-inventions developed by 50 US biotechnology firms from 1985 to 2002. Findings – The authors find that institutional diversity between the partners, as reflected by firm-university partnerships, positively affects the value of their joint-innovation. This effect is reinforced by the firm’s behaviour in searching for knowledge broadly (scope) and in the non-commercial realm (science-based nature). Conversely, as the firm searches for knowledge in few domains areas (depth), the positive effect of institutional diversity is reduced. Research limitations/implications – The study contributes to literature on partner selection, university-industry collaborations, balance between exploration and exploitation, as well as to research on the interdependence between firm’s external and internal resources. Practical implications – The study reveals that when firms innovate together with universities, this promotes the development of high valuable innovations. In addition, it emerges that to fully capture the benefits of these collaborations, firms have to develop a wide set of competencies supported by a scientific approach in problem solving. Originality/value – The study sheds new light on the dynamics favouring the joint development of valuable innovations by focusing on the impact exerted by partners’ institutional differences, as revealed by how norms and rules shape innovation’s modes.

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11

Kirby, Katherine E. "Intercultural Dialogue: in Search of Harmony in Diversity". Journal of Intercultural Studies 39, n.º 1 (12 de diciembre de 2017): 108–10. http://dx.doi.org/10.1080/07256868.2017.1379963.

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Huang, Xin, Hong Cheng, Rong-Hua Li, Lu Qin y Jeffrey Xu Yu. "Top-K structural diversity search in large networks". Proceedings of the VLDB Endowment 6, n.º 13 (29 de agosto de 2013): 1618–29. http://dx.doi.org/10.14778/2536258.2536272.

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Eravci, Bahaeddin y Hakan Ferhatosmanoglu. "Diversity based relevance feedback for time series search". Proceedings of the VLDB Endowment 7, n.º 2 (octubre de 2013): 109–20. http://dx.doi.org/10.14778/2732228.2732230.

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Wang, Xiaojie, Ji-Rong Wen, Zhicheng Dou, Tetsuya Sakai y Rui Zhang. "Search Result Diversity Evaluation Based on Intent Hierarchies". IEEE Transactions on Knowledge and Data Engineering 30, n.º 1 (1 de enero de 2018): 156–69. http://dx.doi.org/10.1109/tkde.2017.2729559.

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15

Palubeckis, Gintaras. "Iterated tabu search for the maximum diversity problem". Applied Mathematics and Computation 189, n.º 1 (junio de 2007): 371–83. http://dx.doi.org/10.1016/j.amc.2006.11.090.

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16

Wang, Hui, Hui Sun, Changhe Li, Shahryar Rahnamayan y Jeng-shyang Pan. "Diversity enhanced particle swarm optimization with neighborhood search". Information Sciences 223 (febrero de 2013): 119–35. http://dx.doi.org/10.1016/j.ins.2012.10.012.

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17

Wu, Zhijing, Ke Zhou, Yiqun Liu, Min Zhang y Shaoping Ma. "Does Diversity Affect User Satisfaction in Image Search". ACM Transactions on Information Systems 37, n.º 3 (20 de julio de 2019): 1–30. http://dx.doi.org/10.1145/3320118.

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Huang, Xin, Hong Cheng, Rong-Hua Li, Lu Qin y Jeffrey Xu Yu. "Top-K structural diversity search in large networks". VLDB Journal 24, n.º 3 (13 de febrero de 2015): 319–43. http://dx.doi.org/10.1007/s00778-015-0379-0.

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19

Tsymbal, Alexey, Mykola Pechenizkiy y Pádraig Cunningham. "Diversity in search strategies for ensemble feature selection". Information Fusion 6, n.º 1 (marzo de 2005): 83–98. http://dx.doi.org/10.1016/j.inffus.2004.04.003.

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20

Ely, Brandon, Winston Koh, Eamen Ho, Tasmina M. Hassan, Anh V. Pham y Weigang Qiu. "Novelty Search Promotes Antigenic Diversity in Microbial Pathogens". Pathogens 12, n.º 3 (28 de febrero de 2023): 388. http://dx.doi.org/10.3390/pathogens12030388.

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Driven by host–pathogen coevolution, cell surface antigens are often the fastest evolving parts of a microbial pathogen. The persistent evolutionary impetus for novel antigen variants suggests the utility of novelty-seeking algorithms in predicting antigen diversification in microbial pathogens. In contrast to traditional genetic algorithms maximizing variant fitness, novelty-seeking algorithms optimize variant novelty. Here, we designed and implemented three evolutionary algorithms (fitness-seeking, novelty-seeking, and hybrid) and evaluated their performances in 10 simulated and 2 empirically derived antigen fitness landscapes. The hybrid walks combining fitness- and novelty-seeking strategies overcame the limitations of each algorithm alone, and consistently reached global fitness peaks. Thus, hybrid walks provide a model for microbial pathogens escaping host immunity without compromising variant fitness. Biological processes facilitating novelty-seeking evolution in natural pathogen populations include hypermutability, recombination, wide dispersal, and immune-compromised hosts. The high efficiency of the hybrid algorithm improves the evolutionary predictability of novel antigen variants. We propose the design of escape-proof vaccines based on high-fitness variants covering a majority of the basins of attraction on the fitness landscape representing all potential variants of a microbial antigen.

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21

Bilimoria, Diana y Kimberly K. Buch. "The Search is On: Engendering Faculty Diversity Through More Effective Search and Recruitment". Change: The Magazine of Higher Learning 42, n.º 4 (30 de junio de 2010): 27–32. http://dx.doi.org/10.1080/00091383.2010.489022.

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22

Singh, Vikram. "Predicting Search Intent Based on In-Search Context for Exploratory Search". International Journal of Advanced Pervasive and Ubiquitous Computing 11, n.º 3 (julio de 2019): 53–75. http://dx.doi.org/10.4018/ijapuc.2019070104.

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Modern information systems are expected to assist users with diverse goals, via exploiting the topical dimension (‘what' the user is searching for) of information needs. However, the intent dimension (‘why' the user is searching) has preferred relatively lesser for the same intention. Traditionally, the intent is an ‘immediate reason, purpose, or goal' that motivates the user search, and captured in search contexts (Pre-search, In-search, Pro-Search), an ideal information system would be able to use. This article proposes a novel intent estimation strategy; based on the intuition that captured intent, and proactively extracts likely results. The captured ‘Pre-search' context adapts query term proximities within matched results beside document-term statistics and pseudo-relevance feedback with user-relevance feedback for In-search. The assessment asserts the superior performance of the proposed strategy over the equivalent on tradeoffs, e.g., novelty, diversity (coverage, topicality), retrieval (precision, recall, F-measure) and exploitation vs exploration.

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23

Denecke, K. "An Architecture for Diversity-aware Search for Medical Web Content". Methods of Information in Medicine 51, n.º 06 (2012): 549–56. http://dx.doi.org/10.3414/me11-02-0022.

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SummaryObjectives: The Web provides a huge source of information, also on medical and health-related issues. In particular the content of medical social media data can be diverse due to the background of an author, the source or the topic. Diversity in this context means that a document covers different aspects of a topic or a topic is described in different ways. In this paper, we introduce an approach that allows to consider the diverse aspects of a search query when providing retrieval results to a user.Methods: We introduce a system architecture for a diversity-aware search engine that allows retrieving medical information from the web. The diversity of retrieval results is assessed by calculating diversity measures that rely upon semantic information derived from a mapping to concepts of a medical terminology. Considering these measures, the result set is diversified by ranking more diverse texts higher.Results: The methods and system architecture are implemented in a retrieval engine for medical web content. The diversity measures reflect the diversity of aspects considered in a text and its type of information content. They are used for result presentation, filtering and ranking. In a user evaluation we assess the user satisfaction with an ordering of retrieval results that considers the diversity measures.Conclusions: It is shown through the evaluation that diversity-aware retrieval considering diversity measures in ranking could increase the user satisfaction with retrieval results.

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24

Linares López, Carlos y Daniel Borrajo. "Adding Diversity to Classical Heuristic Planning". Proceedings of the International Symposium on Combinatorial Search 1, n.º 1 (25 de agosto de 2010): 73–80. http://dx.doi.org/10.1609/socs.v1i1.18171.

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In this paper we propose a new algorithm for solving general two-player turn-taking games that performs symbolic search utilizing binary decision diagrams (BDDs). It consists of two stages: First, it determines all breadth-first search (BFS) layers using forward search and omitting duplicate detection, next, the solving process operates in backward direction only within these BFS layers thereby partitioning all BDDs according to the layers the states reside in. We provide experimental results for selected games and compare to a previous approach. This comparison shows that in most cases the new algorithm outperforms the existing one in terms of runtime and used memory so that it can solve games that could not be solved before with a general approach.

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Draws, Tim, Nava Tintarev y Ujwal Gadiraju. "Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metrics". ACM SIGKDD Explorations Newsletter 23, n.º 1 (26 de mayo de 2021): 50–58. http://dx.doi.org/10.1145/3468507.3468515.

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The way pages are ranked in search results influences whether the users of search engines are exposed to more homogeneous, or rather to more diverse viewpoints. However, this viewpoint diversity is not trivial to assess. In this paper, we use existing and novel ranking fairness metrics to evaluate viewpoint diversity in search result rankings. We conduct a controlled simulation study that shows how ranking fairness metrics can be used for viewpoint diversity, how their outcome should be interpreted, and which metric is most suitable depending on the situation. This paper lays out important groundwork for future research to measure and assess viewpoint diversity in real search result rankings.

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Wang, Dan, Congcong Xiong y Wei Huang. "Group Search Optimizer for the Mobile Location Management Problem". Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/430705.

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We propose a diversity-guided group search optimizer-based approach for solving the location management problem in mobile computing. The location management problem, which is to find the optimal network configurations of management under the mobile computing environment, is considered here as an optimization problem. The proposed diversity-guided group search optimizer algorithm is realized with the aid of diversity operator, which helps alleviate the premature convergence problem of group search optimizer algorithm, a successful optimization algorithm inspired by the animal behavior. To address the location management problem, diversity-guided group search optimizer algorithm is exploited to optimize network configurations of management by minimizing the sum of location update cost and location paging cost. Experimental results illustrate the effectiveness of the proposed approach.

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Roberts, Mark, Adele Howe y Indrajit Ray. "Evaluating Diversity in Classical Planning". Proceedings of the International Conference on Automated Planning and Scheduling 24 (11 de mayo de 2014): 253–61. http://dx.doi.org/10.1609/icaps.v24i1.13649.

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Applications that require alternative plans challenge the single solution, single quality metric assumptions upon which many classical planners are designed and evaluated. To evaluate the distinctness of alternative plans (i.e., plan sets), researchers have created diversity metrics that often measure the set difference between the actions of plans. Many approaches for generating plan sets embed the same diversity metric in a weighted evaluation function to guide the search mechanism, thus confounding the search process with its evaluation. We discover that two diversity metrics fail to distinguish similar plans from each other or to identify plans with extraneous actions, so we introduce two new diversity metrics, \emph{uniqueness} and \emph{overlap}, to capture these cases. We then examine the tradeoffs of producing diverse plans while we control for plan length and metric interaction and confirm that metric interaction can significantly impact search performance. We show that planners searching for plan sets must consider a third metric, \emph{parsimony}, that prefers shorter plans while maximizing diversity.We evaluate three existing approaches for generating diverse plans and two new algorithms that are designed to explicitly manage diversity and interaction between the diversity and quality metrics. Our findings synthesize and extend recent results in plan diversity.

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Casas-Martínez, Pedro, Alejandra Casado-Ceballos, Jesús Sánchez-Oro y Eduardo G. Pardo. "Multi-Objective GRASP for Maximizing Diversity". Electronics 10, n.º 11 (22 de mayo de 2021): 1232. http://dx.doi.org/10.3390/electronics10111232.

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This work presents a novel greedy randomized adaptive search procedure approach for dealing with the maximum diversity problem from a multi-objective perspective. In particular, five of the most extended diversity metrics were considered, with the aim of maximizing all of them simultaneously. The metrics considered have been proven to be in conflict, i.e., it is not possible to optimize one metric without deteriorating another one. Therefore, this results in a multi-objective optimization problem where a set of efficient solutions that are diverse with respect to all the metrics at the same time must be obtained. A novel adaptation of the well-known greedy randomized adaptive search procedure, which has been traditionally used for single-objective optimization, was proposed. Two new constructive procedures are presented to generate a set of efficient solutions. Then, the improvement phase of the proposed algorithm consists of a new efficient local search procedure based on an exchange neighborhood structure that follows a first improvement approach. An effective exploration of the exchange neighborhood structure is also presented, to firstly explore the most promising ones. This feature allowed the local search proposed to limit the size of the neighborhood explored, resulting in an efficient exploration of the solution space. The computational experiments showed the merit of the proposed algorithm, when comparing the obtained results with the best previous method in the literature. Additionally, new multi-objective evolutionary algorithms derived from the state-of-the-art were also included in the comparison, to prove the quality of the proposal. Furthermore, the differences found were supported by non-parametric statistical tests.

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Llado-Farrulla, Monica, Joshua Fosnot, Javier Couto, Benjamin Chang, Robyn B. Broach, Arturo Rios-Diaz, Jessica A. Fowler, Cary B. Aarons, Joseph M. Serletti y Paris D. Butler. "In Search of Workforce Diversity? A Program’s Successful Approach". Plastic & Reconstructive Surgery 147, n.º 5 (27 de abril de 2021): 1229–33. http://dx.doi.org/10.1097/prs.0000000000007881.

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30

Fuller, Michael M. "In a World of Diversity, a Search for Unity". Ecology 87, n.º 10 (octubre de 2006): 2681–82. http://dx.doi.org/10.1890/0012-9658(2006)87[2681:iawoda]2.0.co;2.

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31

Mckinney, Arlise P. y Jennifer D. Oyler. "In Search of a Diversity Text: A Critical Review". Academy of Management Learning & Education 7, n.º 3 (septiembre de 2008): 419–23. http://dx.doi.org/10.5465/amle.2008.37029207.

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32

Levine, James S. y Nelleke Gerritsen. "Russian Reflexive Verbs. In Search of Unity in Diversity". Slavic and East European Journal 37, n.º 4 (1993): 564. http://dx.doi.org/10.2307/308462.

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33

Zhou, Yangming, Jin-Kao Hao y Beatrice Duval. "Opposition-Based Memetic Search for the Maximum Diversity Problem". IEEE Transactions on Evolutionary Computation 21, n.º 5 (octubre de 2017): 731–45. http://dx.doi.org/10.1109/tevc.2017.2674800.

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34

Rogan, José, Max Ramírez, Víctor Muñoz, Juan Alejandro Valdivia, Griselda García, Ricardo Ramírez y Miguel Kiwi. "Diversity driven unbiased search of minimum energy cluster configurations". Journal of Physics: Condensed Matter 21, n.º 8 (30 de enero de 2009): 084209. http://dx.doi.org/10.1088/0953-8984/21/8/084209.

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35

Wang, Dan, Congcong Xiong y Xiankun Zhang. "An Opposition-Based Group Search Optimizer with Diversity Guidance". Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/546181.

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Group search optimizer (GSO) which is an effective evolutionary algorithm has been successfully applied in many applications. However, the purely stochastic resampling or selection mechanism in GSO leads to long computing time and premature convergence. In this paper, we propose a diversity-guided group search optimizer (DGSO) with opposition-based learning (OBL) to overcome these limitations. Opposition-based learning is utilized to accelerate the convergence rate of GSO, while the diversity guidance (DG) is used to increase the diversity of population. When compared with the standard GSO, a novel operator using OBL and DG is developed for the population initialization as well as the generation jumping. A comprehensive set of 19 complex benchmark functions is used for experiment verification and is compared to the original GSO algorithm. Numerical experiments show that the proposed DGSO leads to better performance in comparison with the standard GSO in the convergence rate and the solution accuracy.

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Ostermeier, Marc. "Synthetic gene libraries: in search of the optimal diversity". Trends in Biotechnology 21, n.º 6 (junio de 2003): 244–47. http://dx.doi.org/10.1016/s0167-7799(03)00089-1.

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37

Duarte, Abraham y Rafael Martí. "Tabu search and GRASP for the maximum diversity problem". European Journal of Operational Research 178, n.º 1 (abril de 2007): 71–84. http://dx.doi.org/10.1016/j.ejor.2006.01.021.

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Bueno, Paulo M. S., Mario Jino y W. Eric Wong. "Diversity oriented test data generation using metaheuristic search techniques". Information Sciences 259 (febrero de 2014): 490–509. http://dx.doi.org/10.1016/j.ins.2011.01.025.

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Aringhieri, R. y R. Cordone. "Comparing local search metaheuristics for the maximum diversity problem". Journal of the Operational Research Society 62, n.º 2 (febrero de 2011): 266–80. http://dx.doi.org/10.1057/jors.2010.104.

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40

Di Santo, James P. "Natural killer cells: diversity in search of a niche". Nature Immunology 9, n.º 5 (18 de abril de 2008): 473–75. http://dx.doi.org/10.1038/ni.f.201.

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Aringhieri, Roberto, Roberto Cordone y Yari Melzani. "Tabu Search versus GRASP for the maximum diversity problem". 4OR 6, n.º 1 (13 de marzo de 2007): 45–60. http://dx.doi.org/10.1007/s10288-007-0033-9.

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Suzuki, Osamu. "Search Efforts, Selective Appropriation, and the Usefulness of New Knowledge". International Journal of Knowledge Management 9, n.º 1 (enero de 2013): 42–59. http://dx.doi.org/10.4018/jkm.2013010103.

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Prior research calls for more attention to organizational contexts’ moderating effects on a relationship between diversity in antecedent knowledge and resultant new knowledge generation. The authors examined 11,939 firms granted 103,952 U.S. patents between 1975 and 1999, and found a stronger positive association between the diversity and resultant new knowledge’s degree of usefulness under the context more strongly characterized with extensive search efforts (i.e., U.S. applicants). Under the context more strongly characterized with selective appropriation (i.e., non-U.S. applicants), the study found a weaker inverted U-shape association between the diversity and resultant new knowledge’s variability in usefulness. Author’s findings show that it is important needed to properly control for the effect of such organizational contexts for a more conclusive explanation on the role of antecedent knowledge diversity in new knowledge generation.

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Liu, Zichang, Yongsheng Bai y Xisheng Jia. "Multi-strategy Improved Sparrow Search Algorithm". Journal of Physics: Conference Series 2549, n.º 1 (1 de julio de 2023): 012030. http://dx.doi.org/10.1088/1742-6596/2549/1/012030.

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Abstract The multi-strategy improved sparrow search algorithm (MSISSA) is proposed to address the problems that the sparrow search algorithm (SSA) is not rich in population diversity, and is prone to fall into local optimality and poor accuracy in solving multi-dimensional functions. Firstly, Cat mapping is used to initialize the SSA population. Secondly, an elite reverse learning strategy is introduced to increase the population diversity and improve the global search ability of SSA. Then, the number of discoverers and the number of aware-at-risk sparrows are dynamically adjusted by improving the scaling factor. Finally, individuals are subjected to Cauchy variation or Tent chaos perturbation according to their fitness values to effectively solve the problem of their falling into local optimality. Simulation results show that MSISSA has higher performance in finding the optimum compared with classical optimization algorithms such as SSA.

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Bashir, H. A. "Diversity Control in Evolutionary Computation using Asynchronous Dual-Populations with Search Space Partitioning". Nigerian Journal of Technological Development 17, n.º 3 (29 de octubre de 2020): 175–88. http://dx.doi.org/10.4314/njtd.v17i3.4.

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Diversity control is vital for effective global optimization using evolutionary computation (EC) techniques. This paper classifies the various diversity control policies in the EC literature. Many research works have attributed the high risk of premature convergence to sub-optimal solutions to the poor exploration capabilities resulting from diversity collapse. Also, excessive cost of convergence to optimal solution has been linked to the poor exploitation capabilities necessary to focus the search. To address this exploration-exploitation trade-off, this paper deploys diversity control policies that ensure sustained exploration of the search space without compromising effective exploitation of its promising regions. First, a dual-pool EC algorithm that facilitates a temporal evolution-diversification strategy is proposed. Then a quasi-random heuristic initialisation based on search space partitioning (SSP) is introduced to ensure uniform sampling of the initial search space. Second, for the diversity measurement, a robust convergence detection mechanism that combines a spatial diversity measure; and a population evolvability measure is utilised. It was found that the proposed algorithm needed a pool size of only 50 samples to converge to optimal solutions of a variety of global optimization benchmarks. Overall, the proposed algorithm yields a 33.34% reduction in the cost incurred by a standard EC algorithm. The outcome justifies the efficacy of effective diversity control on solving complex global optimization landscapes. Keywords: Diversity, exploration-exploitation tradeoff, evolutionary algorithms, heuristic initialisation, taxonomy.

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45

Dart, Eric. "Karl Rahner and the Elusive Search for Christian Unity". Religions 9, n.º 11 (17 de noviembre de 2018): 365. http://dx.doi.org/10.3390/rel9110365.

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Despite his prominence within the landscape of theology, Karl Rahner is largely absent in ecumenical discourse. This is surprising considering the concern he shows for both the church’s unity and ecumenism throughout his writings. Rahner’s understanding of unity and diversity and their relationship to one another has the potential to provide important resources for the contemporary ecumenical movement and the goal of visible unity. This article examines Karl Rahner’s theological understanding of ecumenism and the relationship of ecumenism to the realities of unity and diversity. This article explicates Rahner’s theologies of symbol and unity as prerequisites for understanding and developing the relationship between unity and diversity. The unity of the Church is fundamentally a symbolic reality in the process of “becoming”.

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46

Liu, Xiaobo, Kun Li y Huizhi Ren. "A Hybrid Algorithm for the Permutation Flowshop Scheduling Problem without Intermediate Buffers". Discrete Dynamics in Nature and Society 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/548363.

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This paper deals with the permutation flowshop scheduling problem without intermediate buffers and presents a hybrid algorithm based on the scatter search and the variable neighborhood search. In the hybrid algorithm, the solutions with good quality and diversity are maintained by a reference set of scatter search, and the search at each generation starts from a solution generated from the reference set so as to improve the search diversity while guaranteeing the quality of the initial solution. In addition, a variable neighbourhood based on the notion of job-block is developed, and the neighbourhood size can adaptively change according to the construction of the job-block. Such a dynamic strategy can help to obtain a balance between search depth and diversity. Extensive experiments on benchmark problems are carried out and the results show that the proposed hybrid algorithm is powerful and competitive with the other powerful algorithms in the literature.

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47

Schoenung, Benjamin y Desislava Dikova. "Reflections on organizational team diversity research". Equality, Diversity and Inclusion: An International Journal 35, n.º 3 (18 de abril de 2016): 221–31. http://dx.doi.org/10.1108/edi-11-2015-0095.

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Purpose – Research on organizational team diversity operates under the assumption that team diversity matters for organizational team behavior. The purpose of this paper is to outline this assumption by referring to three aspects which this type of research has conventionally employed, that is, the conceptual definition, IPO logic, and the concept’s operationalization. The authors subsequently search for its logical support. Design/methodology/approach – The search covers several pieces of information: the possible origins of organizational team diversity research, models on group composition, and models on collective behavior. Findings – The authors do not find strong evidence in favor of the field’s assumption. Originality/value – The implications of this are put into context with contemporary research practices and diversity’s popularity.

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Han, XiaoHong, Long Quan, XiaoYan Xiong y Bing Wu. "Diversity enhanced and local search accelerated gravitational search algorithm for data fitting with B-splines". Engineering with Computers 31, n.º 2 (20 de octubre de 2013): 215–36. http://dx.doi.org/10.1007/s00366-013-0343-9.

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49

Cheng, Shi, Yuhui Shi, Quande Qin, Qingyu Zhang y Ruibin Bai. "Population Diversity Maintenance In Brain Storm Optimization Algorithm". Journal of Artificial Intelligence and Soft Computing Research 4, n.º 2 (1 de abril de 2014): 83–97. http://dx.doi.org/10.1515/jaiscr-2015-0001.

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Abstract The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature convergence happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a young and promising algorithm in swarm intelligence, is based on the collective behavior of human being, that is, the brainstorming process. The convergence strategy is utilized in BSO algorithm to exploit search areas may contain good solutions. The new solutions are generated by divergence strategy to explore new search areas. Premature convergence also happens in the BSO algorithm. The solutions get clustered after a few iterations, which indicate that the population diversity decreases quickly during the search. A definition of population diversity in BSO algorithm is introduced in this paper to measure the change of solutions’ distribution. The algorithm's exploration and exploitation ability can be measured based on the change of population diversity. Different kinds of partial reinitialization strategies are utilized to improve the population diversity in BSO algorithm. The experimental results show that the performance of the BSO is improved by part of solutions re-initialization strategies.

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50

Baer, Hans A. "Against Relativism: Cultural Diversity and the Search for Ethical Universals in Medicine:Against Relativism: Cultural Diversity and the Search for Ethical Universals in Medicine." American Anthropologist 102, n.º 3 (septiembre de 2000): 669–70. http://dx.doi.org/10.1525/aa.2000.102.3.669.

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