Most clustering algorithms produce a single clustering solution. Similarly, feature selection for clustering tries to find one feature subset where one interesting clustering solution resides. However, a single data set may be multi-faceted and can be grouped and interpreted in many different ways, especially for high dimensional data, where feature selection is typically needed. Moreover, diff...

Recently, multi-view clustering has received much attention in the fields of machine learning and pattern recognition. Spectral for single multiple views been common solution. Despite its good performance, it a major limitation: requires an extra step clustering. This step, which could be famous k-means clustering, depends heavily on initialization, may affect quality result. To overcome this p...

In recent years, collaborative filtering (CF) methods are important and widely accepted techniques are available for recommender systems. One of these techniques is user based that produces useful recommendations based on the similarity by the ratings of likeminded users. However, these systems suffer from several inherent shortcomings such as data sparsity and cold start problems. With the dev...

Incomplete multi-view clustering (IMVC) has attracted remarkable attention due to the emergence of data with missing views in real applications. Recent methods attempt recover information address IMVC problem. However, they generally cannot fully explore underlying properties and correlations similarities across views. This paper proposes a novel Enhanced Tensor Low-rank Sparse Representation R...

• An approach based on NMF of multi-network for multi-view clustering is proposed. factorization with multiple regularizations proposed and developed. Extensive experimental studies were performed real data evaluation. Multi-view has attracted increasing attention in recent years since many sets are usually gathered from different sources or described by feature types. Amongst various existing ...

Incomplete multi-view clustering is an important technique to deal with real-world incomplete data. Previous works assume that all views have the same incompleteness, i.e., balanced incompleteness. However, different often distinct unbalanced which results in strong (low-incompleteness views) and weak (high-incompleteness views). The incompleteness prevents us from directly using previous metho...

In this paper, we describe our experiments of search task for TRECVID 2007. This year we participated in the automatic video search subtask, and submitted six runs with different combination of approaches to NIST. Using the text only based search engine used in last year, the run F_A_1_JTU_FA_1_1 provides a baseline search result list. In order to bring up true relevant results, a multi-view ba...