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IEEE Transactions on Knowledge and Data Engineering
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#1Riccardo Guidotti (UniPi: University of Pisa)H-Index: 9
#2Giulio Rossetti (UniPi: University of Pisa)H-Index: 9
Last.Dino Pedreschi (UniPi: University of Pisa)H-Index: 40
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Nowadays, a hot challenge for supermarket chains is to offer personalized services to their customers. Market basket prediction, i.e., supplying the customer a shopping list for the next purchase according to her current needs, is one of these services. Current approaches are not capable of capturing at the same time the different factors influencing the customer's decision process: co-occurrence, sequentuality, periodicity, and recurrency of the purchased items. To this aim, we define a pattern...
2 CitationsSource
#1Huan Li (ZJU: Zhejiang University)H-Index: 2
#2Hua Lu (AAU: Aalborg University)H-Index: 26
Last.Ke Chen (ZJU: Zhejiang University)H-Index: 2
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Knowing popular indoor locations can benefit many applications like exhibition planning and location-based advertising, among others. In this work, we use uncertain historical indoor mobility data to find the top-k popular indoor semantic locations with the highest flow values. In the data we use, an object positioning report contains a set of samples, each consisting of an indoor location and a corresponding probability. The problem is challenging due to the difficulty in obtaining reliable ...
1 CitationsSource
#1Peter Christen (ANU: Australian National University)H-Index: 31
#2Thilina Ranbaduge (ANU: Australian National University)H-Index: 5
Last.Rainer SchnellH-Index: 19
view all 4 authors...
Being able to identify records that correspond to the same entity across diverse databases is an increasingly important step in many data analytics projects. Research into privacy-preserving record linkage (PPRL) aims to develop techniques that can link records across databases such that besides the record pairs classified as matches no sensitive information about the entities in these databases is revealed. A popular technique used in PPRL is to encode sensitive values into Bloom filters (bit v...
1 CitationsSource
#1Vahid Ranjbar (UT: University of Tehran)H-Index: 1
#2Mostafa Salehi (UT: University of Tehran)H-Index: 10
Last.Mahdi Jalili (RMIT: RMIT University)H-Index: 27
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Complex networks have now become integral parts of modern information infrastructures. This paper proposes a user-centric method for detecting anomalies in heterogeneous information networks, in which nodes and/or edges might be from different types. In the proposed anomaly detection method, users interact directly with the system and anomalous entities can be detected through queries. Our approach is based on tensor decomposition and clustering methods. We also propose a network generation mode...
2 CitationsSource
#1Min Du (UofU: University of Utah)H-Index: 4
#2Feifei Li (UofU: University of Utah)H-Index: 32
System event logs have been frequently used as a valuable resource in data-driven approaches to enhance system health and stability. A typical procedure in system log analytics is to first parse unstructured logs to structured data, and then apply data mining and machine learning techniques and/or build workflow models from the resulting structured data. Previous work on parsing system event logs focused on offline, batch processing of raw log files. But increasingly, applications demand online ...
1 CitationsSource
#1Lu Zhang (UA: University of Arkansas)H-Index: 8
#2Yongkai Wu (UA: University of Arkansas)H-Index: 5
Last.Xintao Wu (UA: University of Arkansas)H-Index: 23
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Anti-discrimination is an increasingly important task in data science. In this paper, we investigate the problem of discovering both direct and indirect discrimination from the historical data, and removing the discriminatory effects before the data are used for predictive analysis (e.g., building classifiers). The main drawback of existing methods is that they cannot distinguish the part of influence that is really caused by discrimination from all correlated influences. In our approach, we mak...
4 CitationsSource
#1Xianpeng Liang (Tongji University)
#2Di Wu (Tongji University)
Last.De-Shuang Huang (Tongji University)H-Index: 49
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Object co-segmentation aims at simultaneously extracting common objects appeared in multiple images. In this paper, we propose a novel object co-segmentation method in which we formulate the image co-segmentation as a locally biased discriminative clustering problem. Specifically, we add a seed vector and a constraint term into the framework of discriminative clustering to constrain the segmentation result bias to this seed vector. In order to deal with the co-segmentation problem with indefinit...
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#1Hosein Azarbonyad (UvA: University of Amsterdam)H-Index: 8
#2Mostafa Dehghani (UvA: University of Amsterdam)H-Index: 10
Last.Maarten de Rijke (UvA: University of Amsterdam)H-Index: 59
view all 6 authors...
A high degree of topical diversity is often considered to be an important characteristic of interesting text documents. A recent proposal for measuring topical diversity identifies three distributions for assessing the diversity of documents: distributions of words within documents, words within topics, and topics within documents. Topic models play a central role in this approach and, hence, their quality is crucial to the efficacy of measuring topical diversity. The quality of topic models is ...
1 CitationsSource
#1Jungeun Kim (KAIST)H-Index: 3
#2Sungsu Lim (CNU: Chungnam National University)H-Index: 5
Last.Byung Suk Lee (UVM: University of Vermont)H-Index: 12
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This paper proposes LinkBlackHole^{*}, a novel algorithm for finding communities that are (i) overlapping in nodes and (ii) mixing (not separating clearly) in links. There has been a small body of work in each category, but this paper is the first one that addresses both. LinkBlackHole^{*} is a merger of our earlier two algorithms, LinkSCAN^{*} and BlackHole, inheriting their advantages in support of highly-mixed overlapping communities. The former is used to handle overlapping nodes, a...
2 CitationsSource
#1Yixiang Fang (HKU: University of Hong Kong)H-Index: 9
#2Zhongran Wang (HIT: Harbin Institute of Technology)H-Index: 1
Last.Jiafeng Hu (HKU: University of Hong Kong)H-Index: 9
view all 5 authors...
Communities are prevalent in social networks, knowledge graphs, and biological networks. Recently, the topic of community search (CS), extracting a dense subgraph containing a query vertex q from a graph, has received great attention. However, existing CS solutions are designed for undirected graphs, and overlook directions of edges which potentially lose useful information carried on directions. In many applications (e.g., Twitter), users’ relationships are often modeled as directed graphs (...
6 CitationsSource
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