Dimensions of Semantic Similarity

Szmeja, Paweł; Ganzha, Maria; Paprzycki, Marcin; Pawłowski, Wiesław

doi:10.1007/978-3-319-67946-4_3

Cited by 4 publications

(2 citation statements)

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“…We note that since no single similarity measure was determined to be best (see Section 5), the comparison process involved each considered similarity measure (i.e., separate ranking for score, separate ranking for degree, etc.). Obviously, an attempt to create a combined similarity measure could have been undertaken (e.g., following the discussion found in [92]). However, this is outside the scope of this contribution.…”

Section: Extracting Common Entities From Graphsmentioning

confidence: 99%

“…Many other approaches to combining metadata and network characteristics were tested, e.g., using the percent difference with the score or the sum with the degree of centrality, etc. (we note that there are almost infinitely many ways to calculate a similarity between two characteristics (see, for instance, [98])). Moreover, multiple popular graph metrics from the previous study [71] were also attempted, i.e., pagerank [99], voterank, closeness centrality [100], betweenness centrality [101], current flow closeness centrality [102], current flow betweenness centrality [102,103].…”

Section: Recallmentioning

confidence: 99%

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Applying Named Entity Recognition and Graph Networks to Extract Common Interests from Thematic Subfora on Reddit

Sawicki,

Ganzha,

Paprzycki

et al. 2024

Applied Sciences

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Reddit is the largest topically structured social network. Existing literature, reporting results of Reddit-related research, considers different phenomena, from social and political studies to recommender systems. The most common techniques used in these works, include natural language processing, e.g., named entity recognition, as well as graph networks representing online social networks. However, large-scale studies that take into account Reddit’s unique structure are scarce. In this contribution, similarity between subreddits is explored. Specifically, subreddit posts (from 3189 subreddits, spanning the year 2022) are processed using NER to build graph networks which are further mined for relations between subreddits. The evaluation of obtained results follows the state-of-the-art approaches used for a similar problem, i.e., recommender system metrics, and applies recall and AUC. Overall, the use of Reddit crossposts discloses previously unknown relations between subreddits. Interestingly, the proposed approach may allow for researchers to better connect their study topics with particular subreddits and shows promise for subreddit similarity mining.

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Section: Extracting Common Entities From Graphsmentioning

confidence: 99%