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Articles 1 - 10 of 10
Full-Text Articles in Computer Engineering
Parallel Cosine Nearest Neighbor Graph Construction, David Anastasiu, George Karypis
Parallel Cosine Nearest Neighbor Graph Construction, David Anastasiu, George Karypis
Faculty Publications
The nearest neighbor graph is an important structure in many data mining methods for clustering, advertising, recommender systems, and outlier detection. Constructing the graph requires computing up to n2 similarities for a set of n objects. This high complexity has led researchers to seek approximate methods, which find many but not all of the nearest neighbors. In contrast, we leverage shared memory parallelism and recent advances in similarity joins to solve the problem exactly. Our method considers all pairs of potential neighbors but quickly filters pairs that could not be a part of the nearest neighbor graph, based on similarity …
Document Clustering, David Anastasiu, Andrea Tagarelli
Document Clustering, David Anastasiu, Andrea Tagarelli
Faculty Publications
In a world flooded with information, document clustering is an important tool that can help categorize and extract insight from text collections. It works by grouping similar documents, while simultaneously discriminating between groups. In this article, we provide a brief overview of the principal techniques used to cluster documents, and introduce a series of novel deep-learning based methods recently designed for the document clustering task. In our overview, we point the reader to salient works that can provide a deeper understanding of the topics discussed.
Efficient Identification Of Tanimoto Nearest Neighbors; All Pairs Similarity Search Using The Extended Jaccard Coefficient, David Anastasiu, George Karypis
Efficient Identification Of Tanimoto Nearest Neighbors; All Pairs Similarity Search Using The Extended Jaccard Coefficient, David Anastasiu, George Karypis
Faculty Publications
Tanimoto, or extended Jaccard, is an important similarity measure which has seen prominent use in fields such as data mining and chemoinformatics. Many of the existing state-of-the-art methods for market basket analysis, plagiarism and anomaly detection, compound database search, and ligand-based virtual screening rely heavily on identifying Tanimoto nearest neighbors. Given the rapidly increasing size of data that must be analyzed, new algorithms are needed that can speed up nearest neighbor search, while at the same time providing reliable results. While many search algorithms address the complexity of the task by retrieving only some of the nearest neighbors, we propose …
A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco
A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco
Faculty Publications
Social media is rapidly becoming the main source of news consumption for users, raising significant challenges to news aggregation and recommendation tasks. One of these challenges concerns the recommendation of very recent news. To tackle this problem, approaches to the prediction of news popularity have been proposed. In this paper, we study the task of predicting news popularity upon their publication, when social feedback is unavailable or scarce, and to use such predictions to produce news rankings. Unlike previous work, we focus on accurately predicting highly popular news. Such cases are rare, causing known issues for standard prediction models and …
Robust Classification Of City Roadway Objects For Traffic Related Applications, Niveditha Bhandary, Charles Mackay, Alex Richards, Ji Tong, David Anastasiu
Robust Classification Of City Roadway Objects For Traffic Related Applications, Niveditha Bhandary, Charles Mackay, Alex Richards, Ji Tong, David Anastasiu
Faculty Publications
The increasing prevalence of video data, particularly from traffic and surveillance cameras, is accompanied by a growing need for improved object detection, tracking, and classification techniques. In order to encourage development in this area, the AI City Challenge, sponsored by IEEE Smart World and NVIDIA, cultivated a competitive environment in which teams from all over the world sought to demonstrate the effectiveness of their models after training and testing on a common dataset of 114,766 unique traffic camera keyframes. Models were constructed for two distinct purposes; track 1 designs addressed object detection, localization and classification, while track 2 designs aimed …
The Nvidia Ai City Challenge, Milind Naphade, David Anastasiu, Anuj Sharma, Vamsi Jagrlamudi, Hyeran Jeon, Kaikai Liu, Ming-Ching Chang, Siwei Lyu, Zeyu Gao
The Nvidia Ai City Challenge, Milind Naphade, David Anastasiu, Anuj Sharma, Vamsi Jagrlamudi, Hyeran Jeon, Kaikai Liu, Ming-Ching Chang, Siwei Lyu, Zeyu Gao
Faculty Publications
Web image analysis has witnessed an AI renaissance. The ILSVRC benchmark has been instrumental in providing a corpus and standardized evaluation. The NVIDIA AI City Challenge is envisioned to provide similar impetus to the analysis of image and video data that helps make cities smarter and safer. In its first year, this Challenge has focused on traffic video data. While millions of traffic video cameras around the world capture data, albeit low-quality, very little automated analysis and value creation results. Lack of labeled data, and trained models that can be deployed at the edge of the city fabric, ensure that …
Optimal Constrained Wireless Emergency Network Antenna Placement, Swapnil Gaikwad, David Anastasiu
Optimal Constrained Wireless Emergency Network Antenna Placement, Swapnil Gaikwad, David Anastasiu
Faculty Publications
Communication is paramount, especially during a natural disaster or other emergency. Even when traditional lines of communication become unavailable, emergency response teams must be able to communicate with each other and the outside world. To facilitate this need, major cities across the United States are deploying wireless emergency networks (WENs) that serve as a secure communication channel between emergency response points (police stations, shelters, food banks, hospitals, etc.) and the outside world. An important question when designing such networks is identifying the locations within the city where access points (APs) should be placed to construct a reliable WEN. We propose …
Efficient Neighborhood Graph Construction For Sparse High Dimensional Data, David Anastasiu
Efficient Neighborhood Graph Construction For Sparse High Dimensional Data, David Anastasiu
Faculty Publications
No abstract provided.
Robust And Agile System Against Fault And Anomaly Traffic In Software Defined Networks, Mihui Kim, Younghee Park, Rohit Kotalwar
Robust And Agile System Against Fault And Anomaly Traffic In Software Defined Networks, Mihui Kim, Younghee Park, Rohit Kotalwar
Faculty Publications
The main advantage of software defined networking (SDN) is that it allows intelligent control and management of networking though programmability in real time. It enables efficient utilization of network resources through traffic engineering, and offers potential attack defense methods when abnormalities arise. However, previous studies have only identified individual solutions for respective problems, instead of finding a more global solution in real time that is capable of addressing multiple situations in network status. To cover diverse network conditions, this paper presents a comprehensive reactive system for simultaneously monitoring failures, anomalies, and attacks for high availability and reliability. We design three …
Impact Of Reviewer Social Interaction On Online Consumer Review Fraud Detection, Kunal Goswami, Younghee Park, Chungsik Song
Impact Of Reviewer Social Interaction On Online Consumer Review Fraud Detection, Kunal Goswami, Younghee Park, Chungsik Song
Faculty Publications
Background Online consumer reviews have become a baseline for new consumers to try out a business or a new product. The reviews provide a quick look into the application and experience of the business/product and market it to new customers. However, some businesses or reviewers use these reviews to spread fake information about the business/product. The fake information can be used to promote a relatively average product/business or can be used to malign their competition. This activity is known as reviewer fraud or opinion spam. The paper proposes a feature set, capturing the user social interaction behavior to identify fraud. …