Sentiment analysis has attracted much attention from both researchers and practitioners as
word-of-mouth (WOM) has a significant influence on consumer behavior. One core task of …

Data distribution has a significant impact on clustering results. This study focuses on the
effect of cluster size distribution on clustering, namely the uniform effect of k-means and …

Cluster analysis has a wide application in many areas, including pattern recognition,
information retrieval, and image processing. In most real-world clustering problems, the …

The issue of whether or not word sense disambiguation (WSD) can improve information
retrieval (IR) results has been intensely debated over the years, with many inconclusive or …

Information retrieval (IR) is one of the most important research and development areas due
to the explosion of digital data and the need of accessing relevant information from huge …

Clustering by fast search and detection of density peaks (DPC, Density Peaks Clustering) is
a relatively novel clustering algorithm published in the Science journal. As a density-based …

The technology of three-dimensional (3D) printing was commercialized in the late 1980s.
Since then, the development of this technology has been dramatically increasing. Moreover …

Spectral clustering is one of the most popular graph clustering algorithms, which achieves
the best performance for many scientific and engineering applications. However, existing …

In this paper, we present a novel unsupervised algorithm for word sense disambiguation
(WSD) at the document level. Our algorithm is inspired by a widely-used approach in the …

While it exists information on about any topic on the web, we know from information retrieval
(IR) evaluation programs that search systems fail to answer to some queries in an effective …