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Editorial: TKDD Special Issue on Interactive Data Exploration and Analytics
Xindong Wu, Charu Aggarwal
Article No.: 1
A Viewable Indexing Structure for the Interactive Exploration of Dynamic and Large Image Collections
Frédéric Rayar, Sabine Barrat, Fatma Bouali, Gilles Venturini
Article No.: 2
Thanks to the capturing devices cost reduction and the advent of social networks, the size of image collections is becoming extremely huge. Many works in the literature have addressed the indexing of large image collections for search purposes....
ATR-Vis: Visual and Interactive Information Retrieval for Parliamentary Discussions in Twitter
Raheleh Makki, Eder Carvalho, Axel J. Soto, Stephen Brooks, Maria Cristina Ferreira De Oliveira, Evangelos Milios, Rosane Minghim
Article No.: 3
The worldwide adoption of Twitter turned it into one of the most popular platforms for content analysis as it serves as a gauge of the public’s feeling and opinion on a variety of topics. This is particularly true of political discussions...
Memory-Efficient and Accurate Sampling for Counting Local Triangles in Graph Streams: From Simple to Multigraphs
Yongsub Lim, Minsoo Jung, U. Kang
Article No.: 4
How can we estimate local triangle counts accurately in a graph stream without storing the whole graph? How to handle duplicated edges in local triangle counting for graph stream? Local triangle counting, which computes the number of triangles...
Studies of the human brain network are becoming increasingly popular in the fields of neuroscience, computer science, and neurology. Despite this rapidly growing line of research, gaps remain on the intersection of data analytics, interactive...
In many areas of science, scientists need to find distinct common characterizations of the same objects and, vice versa, to identify sets of objects that admit multiple shared descriptions. For example, in biology, an important task is to identify...
Modern visual analytic tools promote human-in-the-loop analysis but are limited in their ability to direct the user toward interesting and promising directions of study. This problem is especially acute when the analysis task is exploratory in...
VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data
Jaegul Choo, John Stasko, Haesun Park, Hannah Kim, Edward Clarkson, Zhicheng Liu, Changhyun Lee, Fuxin Li, Hanseung Lee, Ramakrishnan Kannan, Charles D. Stolper
Article No.: 8
In this article, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for...
A Session-Based Approach to Fast-But-Approximate Interactive Data Cube Exploration
Niranjan Kamat, Arnab Nandi
Article No.: 9
With the proliferation of large datasets, sampling has become pervasive in data analysis. Sampling has numerous benefits—from reducing the computation time and cost to increasing the scope of interactive analysis. A popular task in data...
GrammarViz 3.0: Interactive Discovery of Variable-Length Time Series Patterns
Pavel Senin, Jessica Lin, Xing Wang, Tim Oates, Sunil Gandhi, Arnold P. Boedihardjo, Crystal Chen, Susan Frankenstein
Article No.: 10
The problems of recurrent and anomalous pattern discovery in time series, e.g., motifs and discords, respectively, have received a lot of attention from researchers in the past decade. However, since the pattern search space is usually...
Srayan Datta, Eytan Adar
Article No.: 11
Community detection is an oft-used analytical function of network analysis but can be a black art to apply in practice. Grouping of related nodes is important for identifying patterns in network datasets but also notoriously sensitive to input...
Learning to Infer Competitive Relationships in Heterogeneous Networks
Yang Yang, Jie Tang, Juanzi Li
Article No.: 12
Detecting and monitoring competitors is fundamental to a company to stay ahead in the global market. Existing studies mainly focus on mining competitive relationships within a single data source, while competing information is usually distributed...
Clustering is one of the fundamental topics in data mining and pattern recognition. As a prospective clustering method, the subspace clustering has made considerable progress in recent researches, e.g., sparse subspace clustering (SSC) and low...
Data Stream Evolution Diagnosis Using Recursive Wavelet Density Estimators
Edgar S. García Treviño, Muhammad Zaid Hameed, Javier A Barria
Article No.: 14
Data streams are a new class of data that is becoming pervasively important in a wide range of applications, ranging from sensor networks, environmental monitoring to finance. In this article, we propose a novel framework for the online diagnosis...