Collections of scholarly documents are usually not thought of as big data. However, large collections of scholarly documents often have many millions of publications, authors, citations, equations, figures, etc., and large scale related data and ...

Much of the conversation on "big data" is centered on data technologies and analytics platforms and how established companies apply them. While those technologies and platforms are certainly very important for industry incumbents, data analytics is also ...

Relevance of search-results is a key factor for any search engine. In order to return and rank the Web-pages that are most relevant to the query, contemporary search engines use complex ranking functions that depend on hundreds of features. For example, ...

In recent years, social media sites are witnessing an information explosion. Determining the reliability of such a large amount of information is a major area of research. Information provenance (aka, sources or origin) provides a way to measure the ...

We demonstrate GeCo, an online personal data GEnerator and COrruptor that facilitates the creation of realistic personal data ranging from names, addresses, and dates, to social security and credit card numbers, as well as numerical values such as ...

Clustering graph data has gained much attention in recent years, as data represented as graphs is ubiquitous in today's applications. For many applications, besides the mere graph data also further information about the vertices of a graph is available, ...

Online news reading has become the major method to know about the world as web provide more information than other media like TV and radio. However, traditional online news reading interface is inconvenient for many types of people, especially for those ...

We present an end-to-end framework for consumer-centric SLA management of virtualized database servers. The framework facilitates adaptive and dynamic provisioning of the database tier of the software applications based on application-defined policies ...

In a trust network, two users who are connected by a trust relationship tend to have similar interests. Based on this observation, existing trust-aware recommendation methods predict ratings for a target user on unseen items by referencing to ratings of ...

Multivariate time series (MTS) classification is an important topic in time series data mining, and lots of efficient models and techniques have been introduced to cope with it. However, early classification on imbalanced MTS data largely remains an ...

We build a system to extract user interests from Twitter messages. Specifically, we extract interest candidates using linguistic patterns and rank them using four different keyphrase ranking techniques: TFIDF, TextRank, LDA-TextRank, and Relevance-...

The average of the customer ratings on the product, which we call reputation, is one of the key factors in online purchasing decision of a product. There is, however, no guarantee in the trustworthiness of the reputation since it can be manipulated ...

It has long been recognized that search queries are often broad and ambiguous. Even when submitting the same query, different users may have different search intents. Moreover, the intents are dynamically evolving. Some intents are constantly popular ...

As plagiarism of software increases rapidly, there are growing needs for software plagiarism detection systems. In this paper, we propose a software plagiarism detection system using an API-labeled control flow graph (A-CFG) that abstracts the ...

This paper introduces the notion of intelligent SSDs. First, we present the design considerations of intelligent SSDs, and then examine their potential benefits under various settings in data mining applications.

Microblogs play an important role for Online Reputation Management. Companies and organizations in general have an increasing interest in obtaining the last minute information about which are the emerging topics that concern their reputation. In this ...

In computing the similarity of scientific papers, previous text-based and link-based similarity measures look at only a single side of the content and citations. In this paper, we propose a novel approach called SimCC that effectively combines the ...

Traditional relation extraction methods work on manually defined relations and typically expect manually labelled extraction patterns for each relation. This strongly limits the scalability of these systems. In Open Relation Extraction (ORE), the ...

We consider the task of automatically phrasing and computing top-k rankings over the information contained in common knowledge bases (KBs), such as YAGO or DBPedia. We assemble the thematic focus and ranking criteria of rankings by inspecting the ...

Shared Nearest Neighbor Density-based clustering (SNN-DBSCAN) is a robust graph-based clustering algorithm and has wide applications from climate data analysis to network intrusion detection. We propose an incremental extension to this algorithm IncSNN-...