Testing the degree of overlap for the expected value of random intervals

Ramos-Guajardo, Ana Belén; González‐Rodríguez, Gil; Colubi, Ana

doi:10.1016/j.ijar.2019.12.012

Cited by 10 publications

(7 citation statements)

References 30 publications

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“…erefore, when the network has 1/2 of the same nodes, the node overlap is about 33%. In the experiment, according to the account association information provided by some users, we extract 20% of the node pairs from the internetwork node pairs to construct the experimental training set [18]. To evaluate the model reasonably, the NS algorithm and the Grh algorithm, which are currently better in mining associated users, are selected for comparison, the NS algorithm and the Grh algorithm select the node with a larger degree value as the seed node， that is, 10% * N nodes are selected from the top25% node degree values of the network as seed nodes, where N is the total number of network nodes.…”

Section: Results' Analysismentioning

confidence: 99%

Network Data Mining Algorithm of Associated Users Based on Multi-Information Fusion

Wang¹,

Zhang²,

Zhang³

2022

Security and Communication Networks

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To explore how related users can optimize the network mining algorithm, the author proposes a related user mining algorithm based on the fusion of user attributes and user relationships. This method recommends key technical problems and solutions based on information represented by multi-information fusion and explores research on associated user network data mining algorithms. Research has shown that the associated user network data mining algorithm based on multi-information fusion is 65% higher than previous methods. AUMA-MRL has good performance under different network overlaps. Also, since the node embedding of the AUMA-MRL algorithm is obtained by neighborhood sampling, for new nodes in the network, the algorithm can quickly obtain the new node embedding, as well as the similarity vector between the new node and the rest of the nodes in the network, therefore, the associated users of newly added nodes in the network can be quickly mined, and the robustness of the mining algorithm of associated users in the network is enhanced. Compared with the existing classical algorithms, the recall rate of the proposed algorithm is increased by 17.5% on average, which can effectively mine the associated users in the network.

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Section: Results' Analysismentioning

confidence: 99%

Network Data Mining Algorithm of Associated Users Based on Multi-Information Fusion

Wang¹,

Zhang²,

Zhang³

2022

Security and Communication Networks

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“…The Morisita-Horn index was found to be appropriate for measuring the pairwise overlapping distance between phenological curves ( Luna-Nieves et al., 2022 ). There are two other widely accepted measures (or metrics) of overlap between curves: the Jaccard overlap index ( Smith, Solow & Preston, 1996 ; Yue & Clayton, 2005 ) and the Szymkiewicz-Simpson overlap coefficient ( Ramos-Guajardo, González-Rodríguez & Colubi, 2020 ); however, these indices do not represent the intensity and the proportion of overlap of phenological curves. The Jaccard overlapping area index only accounts for the overlapping area of both samples but ignores the area outside of the overlapping area.…”

Section: Discussionmentioning

confidence: 99%

Quantifying phenological diversity: a framework based on Hill numbers theory

Sánchez-Ochoa

González

Arizmendi

et al. 2022

PeerJ

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Background Despite the great concern triggered by the environmental crisis worldwide, the loss of temporal key functions and processes involved in biodiversity maintenance has received little attention. Species are restricted in their life cycles by environmental variables because of their physiological and behavioral properties; thus, the timing and duration of species’ presence and their activities vary greatly between species within a community. Despite the ecological relevance of such variation, there is currently no measure that summarizes the key temporal aspects of biological diversity and allows comparisons of community phenological patterns. Here, we propose a measure that synthesizes variability of phenological patterns using the Hill numbers-based attribute diversity framework. Methods We constructed a new phenological diversity measure based on the aforementioned framework through pairwise overlapping distances, which was supplemented with wavelet analysis. The Hill numbers approach was chosen as an adequate way to define a set of diversity values of different order q, a parameter that determines the sensitivity of the diversity measure to abundance. Wavelet transform analysis was used to model continuous variables from incomplete data sets for different phenophases. The new measure, which we call Phenological Hill numbers (PD), considers the decouplings of phenophases through an overlapping area value between pairs of species within the community. PD was first tested through simulations with varying overlap in phenophase magnitude and intensity and varying number of species, and then by using one real data set. Results PD maintains the diversity patterns of order q as in any other diversity measure encompassed by the Hill numbers framework. Minimum PD values in the simulated data sets reflect a lack of differentiation in the phenological curves of the community over time; by contrast, the maximum PD values reflected the most diverse simulations in which phenological curves were equally distributed over time. PD values were consistent with the homogeneous distribution of the intensity and concurrence of phenophases over time, both in the simulated and the real data set. Discussion PD provides an efficient, readily interpretable and comparable measure that summarizes the variety of phenological patterns observed in ecological communities. PD retains the diversity patterns of order q characteristic of all diversity measures encompassed by the distance-based Hill numbers framework. In addition, wavelet transform analysis proved useful for constructing a continuous phenological curve. This methodological approach to quantify phenological diversity produces simple and intuitive values for the examination of phenological diversity and can be widely applied to any taxon or community’s phenological traits.

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“…Sampling was carried out following measurement rules that prevent α and β errors. (Chi, Glueck, & Muller, 2019;Ramos-Guajardo, González-Rodríguez, & Colubi, 2020). The error limit value is measured using the help of G*Power analysis.…”

Section: Participantmentioning

confidence: 99%

Development and validation of the Zadrian-Ifdil Problem Checklist (ZIPC) for college students

Ardi

Ifdil

Maysitoh

2020

Int. J. Tech. Inn Hum

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The variety of problem conditions and the specific dynamics of college student demographics demands a holistic measurement. Various measurements to reveal the attributes of students' problems have been developed in Indonesia, but they are not optimal because they are still partial. Even though a holistic measurement tool has been developed, its effectiveness is still a matter of debate, especially in measuring instrument duration and the number of items that are too large. The development of the Zadrian-Ifdil Problem Checklist (ZIPC) measuring instrument aims to obtain an effective and efficient measuring tool in identifying problems experienced by students daily. This study consists of three phases: item development, testing, validation, and item revision. The sample involved in this study were 639 people spread all over Indonesia. Analysis and validation of measuring tools using the Rasch model approach. The development and validation results revealed that the student version of ZIP-C was reliable and valid to reveal daily personal problems in 8 variables of problem conditions and 50 items. This measuring tool can be used for research purposes and practice services and mental health interventions by professionals.

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Testing the degree of overlap for the expected value of random intervals

Cited by 10 publications

References 30 publications

Network Data Mining Algorithm of Associated Users Based on Multi-Information Fusion

Network Data Mining Algorithm of Associated Users Based on Multi-Information Fusion

Quantifying phenological diversity: a framework based on Hill numbers theory

Development and validation of the Zadrian-Ifdil Problem Checklist (ZIPC) for college students

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