Academic literature on the topic 'Information aggregation'

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Journal articles on the topic "Information aggregation"

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XU, Z. S. "CORRELATED LINGUISTIC INFORMATION AGGREGATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 17, no. 05 (October 2009): 633–47. http://dx.doi.org/10.1142/s0218488509006182.

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Linguistic information aggregation has received great attention from researchers, and a variety of operators have been developed for aggregating linguistic information. All the existing linguistic information aggregation operators only consider the situations where all the aggregated linguistic arguments are independent, i.e., they only consider the addition of the importance of individual linguistic arguments, however, in some actual situations, the considered linguistic arguments may be correlative. In this paper, we focus on this issue. Motivated by the idea of the well-known Choquet integrals,1 we propose two new linguistic information aggregation operators called the linguistic correlated averaging operator and linguistic correlated geometric operator. In the special cases where the aggregated linguistic arguments are independent, the linguistic correlated averaging operator can be reduced to a variety of traditional linguistic averaging aggregation operators; while the linguistic correlated geometric operator can be reduced to a variety of the traditional linguistic geometric aggregation operators. Furthermore, we extend the above results to accommodate uncertain linguistic environments, and illustrate them with a practical problem.
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Jin, LeSheng, Ronald R. Yager, Jana Špirková, Radko Mesiar, Daniel Paternain, and Humberto Bustince. "OWA aggregation with dual preferences for basic uncertain information." Journal of Intelligent & Fuzzy Systems 40, no. 3 (March 2, 2021): 4535–44. http://dx.doi.org/10.3233/jifs-201374.

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Basic Uncertain Information (BUI) as a newly introduced concept generalized a wide range of uncertain information. The well-known Ordered Weighted Averaging (OWA) operators can flexibly and effectively model bipolar preferences of decision makers over given real valued input vector. However, there are no extant methods for OWA operators to be carried out over given BUI vectors. Against this background, this study firstly discusses the interval transformation for BUI and elaborately explains the reasonability within it. Then, we propose the corresponding preference aggregations for BUI in two different decisional scenarios, the aggregation for BUI vector without original information influencing and the aggregation for BUI vector with original information influencing after interval transformation. For each decisional scenario, we also discuss two different orderings of preference aggregation, namely, interval-vector and vector-interval orderings, respectively. Hence, we will propose four different aggregation procedures of preference aggregation for BUI vector. Some illustrative examples are provided immediately after the corresponding aggregation procedures.
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Morgan, John, and Phillip C. Stocken. "Information Aggregation in Polls." American Economic Review 98, no. 3 (May 1, 2008): 864–96. http://dx.doi.org/10.1257/aer.98.3.864.

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We study information transmission via polling. A policymaker polls constituents, who differ in their information and ideology, to determine policy. Full revelation is an equilibrium in a poll with a small sample, but not with a large one. In large polls, full information aggregation can arise in an equilibrium where constituents endogenously sort themselves into centrists, who respond truthfully, and extremists, who do not. We find polling statistics that ignore strategic behavior yield biased estimators and mischaracterize the poll's margin of error. We construct estimators that account for strategic behavior. Finally, we compare polls and elections. (JEL C42, D83)
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Campbell, Donald E., and Jerry S. Kelly. "Information and preference aggregation." Social Choice and Welfare 17, no. 1 (January 2000): 3–24. http://dx.doi.org/10.1007/pl00007172.

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Yager, Ronald R. "Aggregation of ordinal information." Fuzzy Optimization and Decision Making 6, no. 3 (September 13, 2007): 199–219. http://dx.doi.org/10.1007/s10700-007-9008-8.

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Verma, Rajkumar, and Bhudev Sharma. "Prioritized Information Fusion Method for Triangular Fuzzy Information and Its Application to Multiple Attribute Decision Making." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 02 (April 2016): 265–89. http://dx.doi.org/10.1142/s0218488516500136.

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This study investigates the multiple attribute decision making under triangular fuzzy environment in which the attributes and experts are in different priority level. By combining the idea of quasi arithmetic mean and prioritized weighted average (PWA) operator, we first propose two new prioritized aggregation operators called quasi fuzzy prioritized weighted average (QFPWA) operator and the quasi fuzzy prioritized weighted ordered weighted average (QFPWOWA) operator for aggregating triangular fuzzy information. The properties of the new aggregation operators are studied in detail and their special cases are examined. Furthermore, based on the QFPWA operator and QFPWOWA operator, an approach to deal with multiple attribute decision-making problems under triangular fuzzy environments is developed. Finally, a practical example is provided to illustrate the multiple attribute decision making process.
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Koutlis, Christos, Manos Schinas, Symeon Papadopoulos, and Ioannis Kompatsiaris. "GAP: Geometric Aggregation of Popularity Metrics." Information 11, no. 6 (June 15, 2020): 323. http://dx.doi.org/10.3390/info11060323.

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Estimating and analyzing the popularity of an entity is an important task for professionals in several areas, e.g., music, social media, and cinema. Furthermore, the ample availability of online data should enhance our insights into the collective consumer behavior. However, effectively modeling popularity and integrating diverse data sources are very challenging problems with no consensus on the optimal approach to tackle them. To this end, we propose a non-linear method for popularity metric aggregation based on geometrical shapes derived from the individual metrics’ values, termed Geometric Aggregation of Popularity metrics (GAP). In this work, we particularly focus on the estimation of artist popularity by aggregating web-based artist popularity metrics. Finally, even though the most natural choice for metric aggregation would be a linear model, our approach leads to stronger rank correlation and non-linear correlation scores compared to linear aggregation schemes. More precisely, our approach outperforms the simple average method in five out of seven evaluation measures.
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Ezhilvendan, M., T. Kavitha, S. Chinnadurai, and P. Kumaran. "SIAVA: Secret Information Aggregation Design for Various Applications in Wireless Sensor Networks." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 12, no. 2 (December 28, 2013): 3249–54. http://dx.doi.org/10.24297/ijct.v12i2.3285.

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In general information aggregation design that reduces a large amount of transmission is the most practical technique. In previous studies, homomorphic encryptions have been applied to conceal communication during aggregation such that enciphered data can be aggregated algebraically without decryption. Since aggregators collect data without decryption, adversaries are not able to forge aggregated results by compromising them. However, these schemes are not satisfy multi-application environments. Second, these schemes become insecure in case some sensor nodes are compromised. Third, these schemes do not provide secure counting; thus, they may suffer unauthorized aggregation attacks. Therefore, we propose a new concealed data aggregation scheme extended from Boneh et al.s homomorphic public encryption system. The proposed scheme has three contributions. First, it is designed for a multi-application environment. The base station extracts application-specific data from aggregated cipher texts. Next, it mitigates the impact of compromising attacks in single application environments. Finally, it degrades the damage from unauthorized aggregations. To prove the proposed schemes robustness and efficiency, we also conducted the comprehensive analyses and comparisons in the end.
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Siga, Lucas, and Maximilian Mihm. "Information aggregation in competitive markets." Theoretical Economics 16, no. 1 (2021): 161–96. http://dx.doi.org/10.3982/te3559.

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We study when equilibrium prices can aggregate information in an auction market with a large population of traders. Our main result identifies a property of information—the betweenness property—that is both necessary and sufficient for information aggregation. The characterization provides novel predictions about equilibrium prices in complex, multidimensional environments.
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MIHAELA, COVRIG, TANASESCU PAUL, and MIRCEA IULIAN. "Fuzzy Information Aggregation in Insurance." ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH 52, no. 4/2018 (December 18, 2018): 35–48. http://dx.doi.org/10.24818/18423264/52.4.18.03.

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Dissertations / Theses on the topic "Information aggregation"

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Schulte, Elisabeth. "Information aggregation in organizations." [S.l. : s.n.], 2006. http://nbn-resolving.de/urn:nbn:de:bsz:180-madoc-13540.

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Mulanda, Chilongo D. "Social network effects on information aggregation." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/55264.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 57-58).
In this thesis, we investigated how sociometric information can be used to improve different methods of aggregating dispersed information. We specifically compared four different approaches of information aggregation: vanilla opinion poll, opinion polls where sociometric data is inferred from the population's own perception of social connectivity, opinion polls where sociometric data is obtained independent of the populations beliefs and data aggregation using market mechanisms. On comparing the entropy of the error of between the prediction of each of these different methods with the truth, preliminary results suggest that sociometric data does indeed improve the enterprise of information aggregation. The results also raise interesting questions about the relevance and application of different kinds of sociometric data as well as the somewhat surprising efficiency of information market mechanisms.
by Chilongo D. Mulanda.
M.Eng.
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Han, Simeng. "Statistical Methods for Aggregation of Indirect Information." Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11348.

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How to properly aggregate indirect information is more and more important. In this dissertation, we will present two aspects of the issue: indirect comparison of treatment effects and aggregation of ordered-based rank data.
Statistics
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Lobel, Ilan. "Social networks : rational learning and information aggregation." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/54232.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2009.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 137-140).
This thesis studies the learning problem of a set of agents connected via a general social network. We address the question of how dispersed information spreads in social networks and whether the information is efficiently aggregated in large societies. The models developed in this thesis allow us to study the learning behavior of rational agents embedded in complex networks. We analyze the perfect Bayesian equilibrium of a dynamic game where each agent sequentially receives a signal about an underlying state of the world, observes the past actions of a stochastically-generated neighborhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighborhoods defines the network topology (social network). We characterize equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning -- that is, the conditions under which, as the social network becomes large, the decisions of the individuals converge (in probability) to the right action. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of expansion in observations. This result therefore establishes that, with unbounded private beliefs, there will be asymptotic learning in almost all reasonable social networks. Furthermore, we provide bounds on the speed of learning for some common network topologies. We also analyze when learning occurs when the private beliefs are bounded.
(cont.) We show that asymptotic learning does not occur in many classes of network topologies, but, surprisingly, it happens in a family of stochastic networks that has infinitely many agents observing the actions of neighbors that are not sufficiently persuasive. Finally, we characterize equilibria in a generalized environment with heterogeneity of preferences and show that, contrary to a nave intuition, greater diversity (heterogeneity) 3 facilitates asymptotic learning when agents observe the full history of past actions. In contrast, we show that heterogeneity of preferences hinders information aggregation when each agent observes only the action of a single neighbor.
by Ilan Lobel.
Ph.D.
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Wang, John (John Michael) 1976. "Information aggregation and dissemination in simulated markets." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80140.

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Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (leaf 39).
by John Wang.
S.B.and M.Eng.
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Kotronis, Stelios. "Information aggregation in dynamic markets under ambiguity." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/411958/.

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Does ambiguity affect the efficiency of information aggregation in dynamic markets? To the present day there is a sparse and fragmented literature pointing towards an answer. This Thesis studies dynamic markets under ambiguity and examines under what conditions information gets aggregated. Three particular perspectives are investigated: i) Does information get aggregated when traders are myopic and ambiguity averse? In the first Chapter it is proved that information gets aggregated only when a 'separable under ambiguity' security is traded. In case the security is not 'separable under ambiguity', then there exist markets in which information does not get aggregated. The class of 'separable under ambiguity' securities is proved to be non trivial. Finally, it is proved that even if the security is not 'separable under ambiguity', traders will reach an agreement about the price of the security. ii) Does information get aggregated when traders are strategic and ambiguity averse? By defining appropriately an equilibrium concept for infinite horizon games of incomplete information in a setting with ambiguity, it is proved that in a market with a 'separable under ambiguity' security information gets aggregated in every equilibrium in pure strategies. The second chapter concludes by proving that when the security is not 'separable under ambiguity', then there exists an equilibrium in which information does not get aggregated. iii) Are the previous theoretical predictions met in real life? In the third chapter a laboratory experiment is included. The experimental design follows the theoretical models of the first two chapters. The results of the experiment provide significant evidence in favor of the results of the first two chapters.
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Tam, Wing-yan. "Quality of service routing with path information aggregation." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36782956.

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Tam, Wing-yan, and 譚泳茵. "Quality of service routing with path information aggregation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36782956.

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Suen, Benny (Benny Hung Kit) 1975. "Internet information aggregation using the Context Interchange framework." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/46187.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
by Benny Suen.
B.S.
M.Eng.
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Ozkes, Ali Ihsan. "Essays on hyper-preferences, polarization and information aggregation." Palaiseau, Ecole polytechnique, 2014. https://tel.archives-ouvertes.fr/pastel-01071827/document.

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Dans cette thèse, certains problèmes importants et des propriétés de prise de décision collective sont étudiés. En particulier, d'abord, une propriété de stabilité des règles d'agrégation de préférences est introduite et certaines classes bien connues de règles sont testées à cet égard. Deuxièmement, le mesurage de la polarisation préférentielle est étudié, à la fois théorique et empirique. Enfin, le comportement stratégique dans des situations d'agrégation de l'information est étudié à la lumière d'une sorte de modèle de la rationalité limitée, à la fois théoriquement et expérimentalement. La notion de stabilité étudié dans la première partie de la thèse est imposée en particulier sur les fonctions de bien-être sociale et exige que le résultat de ces fonctions doit être robuste à la réduction de la transmission de préférences qui sont soutenu avoir lieu lorsque les individus présentent un ordre des alternatives lorsque les résultats sont également limités à être ordres. Pour tous profils sociétaux de préférences donné, qui est une collection d'ordres des alternatives, une collection compatible d'ordre des classements est extraite et les résultats des fonctions de bien-être social dans ces deux niveaux sont comparés. Il s'avère qu'aucune règle de notation donne des résultats cohérents, bien qu'il puisse y exister des règles Condorcetien. Mesures de polarisation qui sont étudiées en deuxième partie sont en forme d'agrégation des antagonismes par paires dans une société. La polarisation de l'opinion publique aux États-Unis pour les trois dernières décennies est analysé à la lumière de ce point de vue, en utilisant une mesure de polarisation bien acclamé qui est introduit dans la littérature de l'inégalité des revenus. La conclusion est qu'aucune tendance significative dans l'opinion publique polarisation peut être réclamé à exister au cours des dernières décennies. En outre, une adaptation de la même mesure est montrée à satisfaire des propriétés souhaitables à la place de profils de préférences ordinales lorsque trois alternatives sont considérées. En outre, une mesure qui est en effet l'agrégation des différences par paires entre les préférences des individus est caractérisée axiomatiquement. Dans la dernière partie de la thèse, situations de l'agrégation de l'information telles que décrites comme dans le modèle du jury de Condorcet sont étudiées à la lumière d'une approche de rationalité limitée qui est connue hiérarchie cognitive. Plus précisément, une expérience de laboratoire est exécutée pour tester les prédictions théoriques de la notion d'équilibre symétrique de Nash bayésien. On constate que le comportement en laboratoire n'est pas correctement capturé par ce concept qui suppose une forte notion de la rationalité et de l'homogénéité entre les comportements des individus. Pour mieux décrire les résultats à l'expérience, un nouveau modèle de hiérarchie cognitive est développé et montré à faire mieux que la fois l'approche de la rationalité forte et des modèles précédentes de hiérarchie cognitive. Ce modèle de hiérarchie cognitive endogène est comparé en théorie aux modèles précédents de la hiérarchie cognitive et montré pour améliorer dans certaines catégories de jeux
In this thesis, some important problems and properties of collective decision-making are studied. In particular, first, a stability property of preference aggregation rules is introduced and some well-known classes of rules are tested in this regard. Second, measuring preferential polarization is studied, both theoretically and empirically. Finally, strategic behavior in information aggregation situations is investigated in light of a sort of bounded rationality model, both theoretically and experimentally. The stability notion studied in the first part of the thesis is imposed particularly on social welfare functions and requires that the outcome of these functions should be robust to reduction in preference submission that are argued to take place when individuals submit a ranking of alternatives when the outcomes are also restricted to be rankings. Given the preference profile of a society, that is a collection of rankings of alternatives, a compatible collection of rankings of rankings are extracted and the outcome of social welfare functions in these two levels are compared. It turns out that no scoring rule gives consistent results, although there might exist Condorcet-type rules. Polarization measures studied in second part are in form of aggregation of pairwise antagonisms in a society. The public opinion polarization in the United States for the last three decades is analyzed in light of this view, by using a well-acclaimed measure of polarization introduced in the literature of income inequality. The conclusion is that no significant trend in public opinion polarization can be claimed to exist over the last several decades. Also, an adaptation of the same measure is shown to satisfy desirable properties in lieu of ordinal preference profiles when three alternatives are considered. Furthermore, a measure that is the aggregation of pairwise differences among individuals' preferences is characterized by a set of axioms. In the final part of the thesis, information aggregation situations described as in Condorcet jury model is studied in light of cognitive hierarchy approach to bounded rationality. Specifically, a laboratory experiment is run to test the theoretical predictions of the symmetric Bayesian Nash equilibrium concept. It is observed that behavior in lab is not correctly captured by this concept that assumes a strong notion of rationality and homogeneity among individuals' behaviors. To better describe the findings in the experiment, a novel model of cognitive hierarchy is developed and shown to perform better than both strong rationality approach and previous cognitive hierarchy models. This endogenous cognitive hierarchy model is compared theoretically to previous models of cognitive hierarchy and shown to improve in certain classes of games
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Books on the topic "Information aggregation"

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Xu, Zeshui, and Xiaoqiang Cai. Intuitionistic Fuzzy Information Aggregation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3.

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Bouchon-Meunier, Bernadette, ed. Aggregation and Fusion of Imperfect Information. Heidelberg: Physica-Verlag HD, 1998. http://dx.doi.org/10.1007/978-3-7908-1889-5.

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Bouchon-Meunier, Bernadette. Aggregation and Fusion of Imperfect Information. Heidelberg: Physica-Verlag HD, 1998.

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Chowdhry, Bhagwan. Information aggregation, security design, and currency swaps. Cambridge, MA: National Bureau of Economic Research, 2002.

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Xiaoqiang, Cai, and SpringerLink (Online service), eds. Intuitionistic Fuzzy Information Aggregation: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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Angeletos, Marios. Crises and prices: Information aggregation, multiplicity and volatility. Cambridge, Mass: Massachusetts Institute of Technology, Dept. of Economics, 2004.

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Angeletos, Marios. Crises and prices: Information aggregation, multiplicity and volatility. Cambridge, Mass: National Bureau of Economic Research, 2004.

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Angeletos, Marios. Crises and prices: Information aggregation, multiplicity and volatility. Cambridge, MA: National Bureau of Economic Research, 2004.

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Brogan, Martha L. A survey of digital library aggregation services. Washington, D.C: Digital Library Federation, Council on Library and Information Resources, 2003.

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Holmström, Bengt. Aggregation and linearity in the provision of intertemporal incentives. Stanford, Calif: Institute for Mathematical Studies in the Social Sciences, Stanford University, 1985.

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Book chapters on the topic "Information aggregation"

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Wygralak, Maciej. "Aggregation of Information and Aggregation Operators." In Intelligent Counting Under Information Imprecision, 93–109. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34685-9_4.

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Herrera, F., E. Herrera-Viedma, and L. Martinez. "Representation Models for Aggregating Linguistic Information: Issues and Analysis." In Aggregation Operators, 245–59. Heidelberg: Physica-Verlag HD, 2002. http://dx.doi.org/10.1007/978-3-7908-1787-4_8.

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Xu, Zeshui, and Xiaoqiang Cai. "Intuitionistic Fuzzy Information Aggregation." In Intuitionistic Fuzzy Information Aggregation, 1–102. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3_1.

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Jordan, James. "Information Aggregation and Prices." In The New Palgrave Dictionary of Economics, 6484–90. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_2811.

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Jordan, James. "Information Aggregation and Prices." In The New Palgrave Dictionary of Economics, 1–7. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_2811-1.

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Xu, Zeshui, and Xiaoqiang Cai. "Interval-Valued Intuitionistic Fuzzy Information Aggregation." In Intuitionistic Fuzzy Information Aggregation, 103–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3_2.

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Xu, Zeshui, and Xiaoqiang Cai. "Correlation, Distance and Similarity Measures of Intuitionistic Fuzzy Sets." In Intuitionistic Fuzzy Information Aggregation, 151–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3_3.

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Xu, Zeshui, and Xiaoqiang Cai. "Decision Making Models and Approaches Based on Intuitionistic Preference Relations." In Intuitionistic Fuzzy Information Aggregation, 189–248. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3_4.

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Xu, Zeshui, and Xiaoqiang Cai. "Projection Model-Based Approaches to Intuitionistic Fuzzy Multi-Attribute Decision Making." In Intuitionistic Fuzzy Information Aggregation, 249–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3_5.

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Xu, Zeshui, and Xiaoqiang Cai. "Dynamic Intuitionistic Fuzzy Multi-Attribute Decision Making." In Intuitionistic Fuzzy Information Aggregation, 259–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29584-3_6.

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Conference papers on the topic "Information aggregation"

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Stucken, Sebastian, Fahrettin Gokgoz, and Hans-Christian Schmitz. "Tactical information aggregation." In 2021 International Conference on Military Communication and Information Systems (ICMCIS). IEEE, 2021. http://dx.doi.org/10.1109/icmcis52405.2021.9486412.

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Geiger, Bernhard C., and Christoph Temmel. "Information-preserving Markov aggregation." In 2013 IEEE Information Theory Workshop (ITW 2013). IEEE, 2013. http://dx.doi.org/10.1109/itw.2013.6691265.

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Wen Jiang and Milos Zefran. "Coverage control with information aggregation." In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, 2013. http://dx.doi.org/10.1109/cdc.2013.6760742.

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Iyer, Krishnamurthy, Ramesh Johari, and Ciamac C. Moallemi. "Information aggregation in smooth markets." In the 11th ACM conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1807342.1807373.

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Panwar, Gaurav, Reza Tourani, Satyajayant Misra, and Abderrahmen Mtibaa. "Request aggregation." In ICN '17: 4th International Conference on Information-Centric Networking. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3125719.3132110.

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Vivona, Doretta, and Maria Divari. "Aggregation operators of general aimed information." In 7th conference of the European Society for Fuzzy Logic and Technology. Paris, France: Atlantis Press, 2011. http://dx.doi.org/10.2991/eusflat.2011.82.

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Miletitch, Roman, Vito Trianni, Alexandre Campo, and Marco Dorigo. "Information Aggregation Mechanisms in Social Odometry." In European Conference on Artificial Life 2013. MIT Press, 2013. http://dx.doi.org/10.7551/978-0-262-31709-2-ch016.

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Abernethy, Jacob, Sindhu Kutty, Sébastien Lahaie, and Rahul Sami. "Information aggregation in exponential family markets." In EC '14: ACM Conference on Economics and Computation. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2600057.2602896.

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Li, Tongxin, Yue Chen, Bo Sun, Adam Wierman, and Steven Low. "Information Aggregation for Constrained Online Control." In SIGMETRICS '21: ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3410220.3461737.

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Pedronette, Daniel Carlos Guimaraes, and Ricardo da S. Torres. "Exploiting contextual information for rank aggregation." In 2011 18th IEEE International Conference on Image Processing (ICIP 2011). IEEE, 2011. http://dx.doi.org/10.1109/icip.2011.6116726.

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Reports on the topic "Information aggregation"

1

Fair, Ray, and Robert Shiller. Econometric Modeling as Information Aggregation. Cambridge, MA: National Bureau of Economic Research, May 1987. http://dx.doi.org/10.3386/w2233.

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Albagli, Elias, Christian Hellwig, and Aleh Tsyvinski. Information Aggregation, Investment, and Managerial Incentives. Cambridge, MA: National Bureau of Economic Research, August 2011. http://dx.doi.org/10.3386/w17330.

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Hassan, Tarek, and Thomas Mertens. Information Aggregation in a DSGE Model. Cambridge, MA: National Bureau of Economic Research, June 2014. http://dx.doi.org/10.3386/w20193.

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Yager, Ronald R. Information Fusion and Aggregation for Cooperative Systems. Fort Belvoir, VA: Defense Technical Information Center, May 2007. http://dx.doi.org/10.21236/ada486686.

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Chowdhry, Bhagwan, Mark Grinblatt, and David Levine. Information Aggregation, Security Design and Currency Swaps. Cambridge, MA: National Bureau of Economic Research, January 2002. http://dx.doi.org/10.3386/w8746.

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Kung, Fan-chin, and Ping Wang. Information Aggregation and Transmission in Strategic Networks. Cambridge, MA: National Bureau of Economic Research, October 2022. http://dx.doi.org/10.3386/w30585.

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Angeletos, George-Marios, and Ivan Werning. Crises and Prices: Information Aggregation, Multiplicity and Volatility. Cambridge, MA: National Bureau of Economic Research, December 2004. http://dx.doi.org/10.3386/w11015.

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Wallsten, Thomas S. Workshop on Information Aggregation in Group and Individual Decision Making. Fort Belvoir, VA: Defense Technical Information Center, May 2003. http://dx.doi.org/10.21236/ada423004.

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Trammell, B., A. Wagner, and B. Claise. Flow Aggregation for the IP Flow Information Export (IPFIX) Protocol. RFC Editor, September 2013. http://dx.doi.org/10.17487/rfc7015.

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Banerjee, Abhijit, and Olivier Compte. Consensus and Disagreement: Information Aggregation under (not so) Naive Learning. Cambridge, MA: National Bureau of Economic Research, April 2022. http://dx.doi.org/10.3386/w29897.

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