CIKM

For decades, scientists bemoaned the scarcity of observational data to analyze and against which to test their models. Exponential growth in data volumes from ever-cheaper environmental sensors has provided scientists with the answer to their prayers: "...

Multiple source code files reference metadata of an existing database. Consequently, any modification that needs to be done in the source code files or in the schema of a database requires asserting the impact of performing such change. This problem of ...

Science is more and more data-driven. This means, that a significant part of a scientist's work is dedicated to accessing, visualizing, integrating and analyzing data from a possibly wide range of heterogeneous sources. In this paper we propose SciQL, a ...

Networks that model relationships in the real world have attracted much attention in the past few years. Link prediction plays a central role in the network area. Supervised learning is an important class of algorithms used to address the link ...

When faced with a document collection of substantial size, it is difficult for users to explore and analyze the information contained in it. Tagging has been used to improve the organization of documents in a collection, but it has various limitations. ...

Activity mining in traffic scenes aims to automatically explain the complex interactions among moving objects recorded with a surveillance camera. Traditional machine learning algorithms generate a model and validate it with manually labeled data, which ...

This talk will look at the task of pursuing a PhD with both a humorous and a serious eye -- while checking Facebook with yet another one. The goal is threefold: to give practical advice, to take a step back and look at the meaning at it all, and to ...

Automatic detection of communities (or cohesive groups of actors in social network) in online social media platforms based on user interests and interaction is a problem that has recently attracted a lot of research attention. Mining user interactions ...

Investigations on search processes can either be at macro-level or micro-level. The macro-level investigation focuses on establishing theoretical models while micro-level investigation focuses on the user actions. In this paper, we propose using search ...

Searching information by using search engines and browsers is a tedious task for users. Navigational and informational search tasks are complicated by the fact that web servers always provide complete web pages and do not tailor their content to the ...

Linked Data offers new opportunities for Semantic Web-based application development by connecting structured information from various domains. These technologies allow machines and software agents to automatically interpret and consume Linked Data and ...

This paper presents a data-driven approach for capturing the temporal variations in user search behaviour by modeling the dynamic query relationships using query-log data. The dependence between different queries (in terms of the query words and latent ...

This paper presents an advanced system for real-time event detection in high-volume data streams. Our main goal is to provide a system, which can handle high-volume data streams and is able to detect events in real-time. Additionally, we perform further ...

Conceptual models organize the data as well as the processes from a business domain using a human-readable, yet formal representation language. For static data models, various modeling approaches have been proposed to represent complex multilevel ...

Knowing what potential clients want, is the most important issue for companies. The current situation of social communication is generating a lot of information about users, such as favourite sites, food, politic tendencies, hopes or needs. This ...