Updated News Around the World

Algorithms developed to tackle tenuous group query

The most tenuous group query
Graphical abstract. Credit: Frontiers of Computer Science (2022). DOI: 10.1007/s11704-022-1462-5

Finding tenuous groups, those with few social interactions and weak relationships among members, has been a hot topic in community search for reviewer selection and psycho-educational group formation. The existing metrics (e.g., k-triangle, k-line, and k-tenuity) used to measure the tenuity require a suitable k value to be specified, which is difficult for users without background knowledge.

A research team led by Huaijie Zhu has proposed several approaches to tackle this problem. The first is an exact algorithm, named MTG-VDIS, which selects those vertices whose vertex distance is large to generate the result group. It also utilizes effective filtering and pruning strategies.

Since MTG-VDIS is not fast enough, the team designed an efficient exact algorithm, called MTG-VDGE, which exploits the degree metric to sort the vertexes and proposes a new combination order, namely degree and reverse based branch and bound (DRBB). MTG-VDGE gives priority to those vertices with a small degree. For a large p, the team developed an approximation algorithm, named MTG-VDLT, that discards candidate attendees with high degree to reduce the number of vertices to be considered.

The algorithms are published in Frontiers of Computer Science.

In the experiments, the researchers compared the proposed algorithms with the following performance metrics: (1) query time, (2) distance of the result, (3) average group distance of the result, (4) the accuracy score S of the result of the approximation algorithm.

They also conducted a case study to show the usefulness of MTG-VDLT and MTG-VDGE on LA dataset. Experimental results on real datasets manifest that MTG-VDGE outperforms MTG-VDIS in efficiency. For MTG-VDLT, compared with KLMA, the result obtained by MTG-VDLT has a higher accuracy score.

Future work may focus on finding more suitable and flexible metrics to obtain a tenuous group, such as using a machine-learning based method to learn the k value from users’ history data.

More information:
Na Li et al, The most tenuous group query, Frontiers of Computer Science (2022). DOI: 10.1007/s11704-022-1462-5

Provided by
Frontiers Journals

Citation:
Algorithms developed to tackle tenuous group query (2023, May 15)
retrieved 15 May 2023
from https://techxplore.com/news/2023-05-algorithms-tackle-tenuous-group-query.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.

For all the latest Technology News Click Here 

 For the latest news and updates, follow us on Google News

Read original article here

Denial of responsibility! NewsUpdate is an automatic aggregator around the global media. All the content are available free on Internet. We have just arranged it in one platform for educational purpose only. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are the owner of the content and do not want us to publish your materials on our website, please contact us by email – [email protected]. The content will be deleted within 24 hours.