Spam detection with a content-based random-walk algorithm

Ortega, F. Javier; Macdonald, Craig; Troyano, José A.; Cruz, Fermín L.

doi:10.1145/1871985.1871994

Cited by 9 publications

(5 citation statements)

References 16 publications

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“…That is, PageRank considers a node as important only if it is recommended (i.e., connected to) by other important nodes in the graph. The same idea has been widely used for separating legitimate pages from spam pages [56]. Similarly, in our problem context, if an API class co-occurs with other important API classes across multiple code segments that are relevant to a programming task, then this API class is also considered to be important for the task.…”

Section: A Development Of Candidate Api Listsmentioning

confidence: 98%

Effective Reformulation of Query for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics

Rahman¹,

Roy²

2018

Preprint

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Software developers frequently issue generic natural language queries for code search while using code search engines (e.g., GitHub native search, Krugle). Such queries often do not lead to any relevant results due to vocabulary mismatch problems. In this paper, we propose a novel technique that automatically identifies relevant and specific API classes from Stack Overflow Q & A site for a programming task written as a natural language query, and then reformulates the query for improved code search. We first collect candidate API classes from Stack Overflow using pseudo-relevance feedback and two term weighting algorithms, and then rank the candidates using Borda count and semantic proximity between query keywords and the API classes. The semantic proximity has been determined by an analysis of 1.3 million questions and answers of Stack Overflow. Experiments using 310 code search queries report that our technique suggests relevant API classes with 48% precision and 58% recall which are 32% and 48% higher respectively than those of the state-of-the-art. Comparisons with two stateof-the-art studies and three popular search engines (e.g., Google, Stack Overflow, and GitHub native search) report that our reformulated queries (1) outperform the queries of the stateof-the-art, and (2) significantly improve the code search results provided by these contemporary search engines.

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Section: A Development Of Candidate Api Listsmentioning

confidence: 98%

Effective Reformulation of Query for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics

Rahman¹,

Roy²

2018

Preprint

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“…For the online voting systems, Benevenuto et al explored YouTube.com to detect spammers who try to increase the reputations of malicious movies by posting a series of responses, and they exploited video attributes (ratings), user attributes (activities), and social-network metrics (clustering coefficient and betweenness) [24]. To enhance the performance of spam detection, several approaches build social-network-based approaches on top of content-based schemes [14,25,26]. Using the network spam-filter features (in-and out-link, cross-link, etc.)…”

Section: A Spam Filteringmentioning

confidence: 99%

How to Fight against SMS-Spam: Structural Approach and Results

Noh¹

2020

IJMLC

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Although the number of different uses for mobile-data networks has grown rapidly, short message service (SMS) remains the primary message-exchange method; in addition, SMS is still necessary since it provides several advantages including the small monetary cost that is incurred per transmission, greater security compared to online social networks (OSNs). Due to the popular status of SMS, SMS spam is a form of communication that can be used to pursue malicious economic intents such as phishing and illegal advertising, or to widely distribute unwanted messages to numerous phone users. In this paper, we explore the effectiveness of using social structural approach. To this end, we introduce a methodology that shows how to expand SMS networks from small SMS datasets to social networks based on real-world datasets and possible SMS-spam attack. Also, we verify the detection effectiveness of our approach by conducting experiments.

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“…The conventional content-based techniques, which scrutinize the textual content of the pages, and the link-based techniques (Zhou and Pei, 2009;Ortega, et al, 2010) have been used but to little avail primarily because the state-of-art spam techniques has evolved and made spam websites appear very similar to bona fide websites in their link structures (Cheng, at al., 2011). Thus, this suggests that anti-spamming efforts may need to take a collaborative approach within the user community.…”

Section: Literature Review Knowledge Sharingmentioning

confidence: 99%

A Formative Evaluation of Rendezvous

Chua

2014

International Journal of Knowledge Management

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Web applications that offer entertainment rarely support knowledge sharing. Conversely, applications that are intended for knowledge sharing rarely offer entertainment. The intent of this paper is therefore to propose the coalescence of knowledge sharing and entertainment in a Web application. The objectives of this paper are twofold: (1) to introduce a prototype called Rendezvous, which serves as a platform for both knowledge sharing and entertainment and (2) to conduct a formative evaluation of Rendezvous by soliciting feedback and its appeal for users' intention to adopt. A two-stage data collection plan was used. First, qualitative feedback was obtained from a group of 38 participants through focus groups. Thereafter, a questionnaire was developed and administered to 124 participants to assess users' intention to adopt. On the whole, the behavioral intention to adopt Rendezvous seems promising. Factors that seemed to influence behavioral intention to adopt included perceived utility, perceived enjoyment, perceived ease of use and social influences.

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Spam detection with a content-based random-walk algorithm

Cited by 9 publications

References 16 publications

Effective Reformulation of Query for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics

Effective Reformulation of Query for Code Search using Crowdsourced Knowledge and Extra-Large Data Analytics

How to Fight against SMS-Spam: Structural Approach and Results

A Formative Evaluation of Rendezvous

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