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Suhas Ranganath
Arizona State University
18Publications
7H-index
140Citations
Publications 18
Newest
#1Suhas Ranganath (ASU: Arizona State University)H-Index: 7
#2Jayaraman J. Thiagarajan (ASU: Arizona State University)H-Index: 10
Last.Cihan Tepedelenlioglu (ASU: Arizona State University)H-Index: 26
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In this paper, we present a unique Android-DSP (AJDSP) application which was built from the ground up to provide mobile laboratory and computational experiences for educational use. AJDSP provides a mobile intuitive environment for developing and running signal processing simulations in a user-friendly. It is based on a block diagram system approach to support signal generation, analysis, and processing. AJDSP is designed for use by undergraduate and graduate students and DSP instructors. Its ex...
2019 in WWW (The Web Conference)
#1Ghazaleh Beigi (ASU: Arizona State University)H-Index: 6
#2Suhas Ranganath (Walmart Labs)H-Index: 7
Last.Huan Liu (ASU: Arizona State University)H-Index: 79
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Predicting signed links in social networks often faces the problem of signed link data sparsity, i.e., only a small percentage of signed links are given. The problem is exacerbated when the number of negative links is much smaller than that of positive links. Boosting signed link prediction necessitates additional information to compensate for data sparsity. According to psychology theories, one rich source of such information is user’s personality such as optimism and pessimism that can help de...
Feb 2, 2018 in WSDM (Web Search and Data Mining)
#1Suhas Ranganath (ASU: Arizona State University)H-Index: 7
#2Ghazaleh Beigi (ASU: Arizona State University)H-Index: 6
Last.Huan Liu (ASU: Arizona State University)H-Index: 79
view all 3 authors...
The emergence of online microfinancing platforms provides new opportunities for people to seek financial assistance from a large number of potential contributors. However, these platforms deal with a huge number of requests, making it hard for the requesters to get assistance for their financial needs. Designing algorithms to identify potential contributors for a given request will assist in satisfying financial needs of requesters and improve the effectiveness of microfinancing platforms. Exist...
#1Suhas Ranganath (ASU: Arizona State University)H-Index: 7
#2Xia Hu (A&M: Texas A&M University)H-Index: 24
Last.Huan Liu (ASU: Arizona State University)H-Index: 79
view all 5 authors...
Social media provides a platform for seeking information from a large user base. Information seeking in social media, however, occurs simultaneously with users expressing their viewpoints by making statements. Rhetorical questions have the form of a question but serve the function of a statement and are an important tool employed by users to express their viewpoints. Therefore, rhetorical questions might mislead platforms assisting information seeking in social media. It becomes difficult to ide...
Millions of people use online e-commerce platforms to search and buy products. Identifying attributes in a query is a critical component in connecting users to relevant items. However, in many cases, the queries have multiple attributes, and some of them will be in conflict with each other. For example, the query "maroon 5 dvds" has two candidate attributes, the color "maroon" or the band "maroon 5", where only one of the attributes can be present. In this paper, we address the problem of resolv...
Jan 1, 2018 in SIGIR (International ACM SIGIR Conference on Research and Development in Information Retrieval)
#1Suhas Ranganath (ASU: Arizona State University)H-Index: 7
#2Suhang Wang (ASU: Arizona State University)H-Index: 15
Last.Huan Liu (ASU: Arizona State University)H-Index: 79
view all 5 authors...
Social media plays a major role in helping people affected by natural calamities. These people use social media to request information and help in situations where time is a critical commodity. However, generic social media platforms like Twitter and Facebook are not conducive for obtaining answers promptly. Algorithms to ensure prompt responders for questions in social media have to understand and model the factors affecting their response time. In this paper, we draw from sociological studies ...
Apr 3, 2017 in WWW (The Web Conference)
#1Suhang Wang (ASU: Arizona State University)H-Index: 15
#2Yilin Wang (ASU: Arizona State University)H-Index: 7
Last.Huan Liu (ASU: Arizona State University)H-Index: 79
view all 6 authors...
The rapid growth of Location-based Social Networks (LBSNs) provides a vast amount of check-in data, which facilitates the study of point-of-interest (POI) recommendation. The majority of the existing POI recommendation methods focus on four aspects, i.e., temporal patterns, geographical influence, social correlations and textual content indications. For example, user's visits to locations have temporal patterns and users are likely to visit POIs near them. In real-world LBSNs such as Instagram, ...
Jan 1, 2017 in SDM (SIAM International Conference on Data Mining)
#1Suhang Wang (ASU: Arizona State University)H-Index: 15
#2Yilin Wang (ASU: Arizona State University)H-Index: 7
Last.Huan LiuH-Index: 79
view all 6 authors...
Feb 12, 2016 in AAAI (National Conference on Artificial Intelligence)
#1Suhas Ranganath (ASU: Arizona State University)H-Index: 7
#2Fred Morstatter (ASU: Arizona State University)H-Index: 12
Last.Huan Liu (ASU: Arizona State University)H-Index: 79
view all 6 authors...
Social media has emerged to be a popular platform for people to express their viewpoints on political protests like the Arab Spring. Millions of people use social media to communicate and mobilize their viewpoints on protests. Hence, it is a valuable tool for organizing social movements. However, the mechanisms by which protest affects the population is not known, making it difficult to estimate the number of protestors. In this paper, we are inspired by sociological theories of protest particip...
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