SERIATION USING ASYMMETRIC PROXIMITY MEASURES

The idea of Belknap's four-valued logic is that modern computers should function normally not only with the true values of the input information, but also under the conditions of inconsistency and incompleteness of true failures. Belknap's logic introduces four true values: T (true - true), F (false - false), N (none - nobody, nothing, none), B (both - the two, not only the one but also the other). For ease of work with these true values, the following designations are introduced: (1, 0, n, b). Belknap's logic can be used to obtain estimates of proximity measures for discrete objects, for which the functions Jaccard and Needhem, Russel and Rao, Sokal and Michener, Hamming, etc. are used. In this case, it becomes possible to assess the proximity, recognition and classification of objects in conditions of uncertainty when the true values are taken from the set (1, 0, n, b). Based on the architecture of the Hamming neural network, neural networks have been developed that allow calculating the distances between objects described using true values (1, 0, n, b). Keywords: four-valued Belknap logic, Belknap computer, proximity assessment, recognition and classification, proximity function, neural network.

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Direction-Aware User Recommendation Based on Asymmetric Network Embedding

ACM Transactions on Information Systems ◽

10.1145/3466754 ◽

2022 ◽

Vol 40 (2) ◽

pp. 1-23

Author(s):

Sheng Zhou ◽

Xin Wang ◽

Martin Ester ◽

Bolang Li ◽

Chen Ye ◽

...

Keyword(s):

Social Networks ◽

Random Walk ◽

Real World ◽

Directed Network ◽

Network Embedding ◽

The Social ◽

Benchmark Datasets ◽

Direction Information ◽

User Recommendation ◽

Asymmetric Proximity

User recommendation aims at recommending users with potential interests in the social network. Previous works have mainly focused on the undirected social networks with symmetric relationship such as friendship, whereas recent advances have been made on the asymmetric relationship such as the following and followed by relationship. Among the few existing direction-aware user recommendation methods, the random walk strategy has been widely adopted to extract the asymmetric proximity between users. However, according to our analysis on real-world directed social networks, we argue that the asymmetric proximity captured by existing random walk based methods are insufficient due to the inbalance in-degree and out-degree of nodes. To tackle this challenge, we propose InfoWalk, a novel informative walk strategy to efficiently capture the asymmetric proximity solely based on random walks. By transferring the direction information into the weights of each step, InfoWalk is able to overcome the limitation of edges while simultaneously maintain both the direction and proximity. Based on the asymmetric proximity captured by InfoWalk, we further propose the qualitative (DNE-L) and quantitative (DNE-T) directed network embedding methods, capable of preserving the two properties in the embedding space. Extensive experiments conducted on six real-world benchmark datasets demonstrate the superiority of the proposed DNE model over several state-of-the-art approaches in various tasks.

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Comparison of Proximity Measures for a Topological Discrimination

Advances in Knowledge Discovery and Management - Studies in Computational Intelligence ◽

10.1007/978-3-319-45763-5_5 ◽

2016 ◽

pp. 85-99

Author(s):

Rafik Abdesselam ◽

Fatima-Zahra Aazi

Keyword(s):

Proximity Measures

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Proximity Measures

Chapman & Hall/CRC Computer Science & Data Analysis - Exploratory Data Analysis with MATLAB ◽

10.1201/9780203483374.axa ◽

2004 ◽

Keyword(s):

Proximity Measures

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Export Product Scope of Russian Firms and Proximity to Local Comparative Advantages

Economic Policy ◽

10.18288/1994-5124-2021-1-56-81 ◽

2021 ◽

Vol 16 (1) ◽

pp. 56-81

Keyword(s):

Russian Regions ◽

Economic Activities ◽

Manufacturing Enterprises ◽

Comparative Advantages ◽

Product Scope ◽

Policy Measures ◽

Proximity Measures ◽

The Given ◽

The Relationship ◽

Export Product

This paper explores the relationship between the structure of regional comparative advantages and the dynamics of the export product scope of Russian manufacturing enterprises. For this purpose, indices of revealed technological proximity of industries are calculated on the basis of data on types of economic activities and the export product scope of Russian enterprises. The methodology for calculating these indicators is based on the assumption that technologically closer types of activities are, to a certain degree, more often co-produced and co-exported within the boundaries of individual enterprises. This measure of technological proximity has several advantages over the traditionally used indicators. Estimates show that the constructed indices reflect different aspects of technological proximity of industries and can be considered as composite indicators. Technological proximity measures are used to calculate the index of product proximity to the structure of export comparative advantages of Russian regions. This index is statistically related to the probability of a product being included in the export product scope of a Russian exporter, to the probability of the product being excluded from the export product scope and, as a result, to the value and dynamics of exports of this product by the regional enterprises. These findings indicate that there is a relationship between the current structure of the regional comparative advantage and the direction in which the range of exports of Russian enterprises located in this region evolves. The results of the study can be used for designing economic policy measures aimed at diversification of production and export of the Russian regions, in particular on the basis of existing producers and exporters, as well as applied by the firms themselves to detect the most promising directions of activity expansion taking into account the production structure of the region which the given firm is located at.

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