In this article, we briefly summarize the motivation, content and structure of the CNIKM'09 workshop.

This demo describes the OSSOBOOK database system developed for archaeozoology applications providing data storage, data retrieval, and data mining facilities. It shows a case study of integrating state-of-the-art database concepts like intermittently ...

Collaborative tagging systems allow users to label online resources. The tags are generally correlated and evolving according to the change of web contents, and the popularity of tags represent evolution of social interests. Tag taxonomy is a promising ...

World Wide Web content continuously grows in size and importance. Furthermore, users ask Web search engines to satisfy increasingly disparate information needs. New techniques and tools are constantly developed aimed at assisting users in the ...

In this paper we propose a term clustering approach to improve the performance of sentence retrieval in Question Answering (QA) systems. As the search in question answering is conducted over smaller segments of data than in a document retrieval task, ...

Matching person names plays an important role in many applications, including bibliographic databases and indexing systems. Name variations and spelling errors make exact string matching problematic; therefore, it is useful to develop methodologies that ...

Over the past several years, there has been a great interest in topic detection and tracking (TDT). Recently, analyzing general research trend from the huge amount of history documents also arouses considerable attention. However, existing work on TDT ...

Recent technological advances in mobile-based access to social networking platforms and facilities to update information in real{time (e.g. in Facebook) have allowed an individual's online presence to be as ephemeral and dynamic in nature, as her very ...

This paper presents an unsupervised approach to aspect-based opinion polling from raw textual reviews without explicit ratings. The key contribution of this paper is three-fold. First, a multi-aspect bootstrapping algorithm is proposed to learn from ...

Clustering ensembles combine different clustering solutions into a single robust and stable one. Most of existing methods become highly time-consuming when the data size turns to large. In this paper, we study the properties of the defined 'clustering ...

Clusters of text documents output by clustering algorithms are often hard to interpret. We describe motivating real-world scenarios that necessitate reconfigurability and high interpretability of clusters and outline the problem of generating ...

To increase the relevancy of local patterns discovered from noisy relations, it makes sense to formalize error-tolerance. Our starting point is to address the limitations of state-of-the-art methods for this purpose. Some extractors perform an ...

This paper introduces a clustering approach, XML Clustering using Frequent Substructures (XCFS) that considers both the structural and the content information of XML documents in clustering. XCFS uses frequent substructures in the form of a novel ...

Tourist photographs constitute a large part of the images uploaded to photo sharing platforms. But filtering methods are needed before one can extract useful knowledge from noisy user-supplied metadata. Here we show how to extract clean trip related ...

This paper proposes the integration of semantic information drawn from a web application's domain knowledge into all phases of the web usage mining process (preprocessing, pattern discovery, and recommendation/prediction). The goal is to have an ...

Given an author-conference graph, how do we answer proximity queries (e.g., what are the most related conferences for John Smith?); how can we tailor the search result if the user provides additional yes/no type of feedback (e.g., what are the most ...

Many outlier detection methods do not merely provide the decision for a single data object being or not being an outlier but give also an outlier score or "outlier factor" signaling "how much" the respective data object is an outlier. A major problem ...