Multi-tenant is the key feature for SaaS application, however, the traditional indexing mechanism has failed in multi-tenant shared scheme database. This paper proposed a multi-tenant distributed indexing mechanism. We create a global index first and then create the local index by MapReduce framework based on Hadoop. We also proposed the process of index update and index merging. Experimental r...

In this paper, we present a clustering-based color indexing scheme for effective amd efficient image retrieval, which is essentially an exploration on the application of clustering technique to image retrieval. In our approach, the color features are clustered automatically using a color clustering algorithm twice (called two-level clustering processing) and two color feature summarizations are...

Database tuning is a common problem, but it requires much knowledge about the characteristics of the database system and the expected workload. Dynamically changing workload complicates the search for the perfect settings. In this contribution we present several approaches that autonomously examine the operations and adjust different parameters. Even though different tools for this task are ava...

This paper proposes the use of a vector of color histogram peaks as an efficient and effective way for many image indexing problems. It shows that histogram peaks are more stable than general histogram bins when there are variation of scale and/or scale. We also introduce the structure of a room recognition system which applies this indexing technique to omni-directional images of rooms. Experi...

We describe in this paper the MUMIS Project (Multimedia Indexing and Searching Environment)1 and show the role linguistically motivated annotations, coupled with domain-specific information, can play for the indexing and the searching of multimedia (and multilingual) data. MUMIS develops and integrates base technologies, demonstrated within a laboratory prototype, to support automated multimedi...

This paper demonstrates the use of generalized partial indexes for efficient query processing. We propose that partial indexes be built on those portions of the database that are statistically likely to be the most useful for query processing. We identify three classes of statistical information, and two levels at which it may be available. We describe indexing strategies that use this informat...

Based on the selected corpus of journals, this paper aims to analyse criteria for their inclusion in bibliographic and citation database Scopus. The takes a sample three scientific journals from Bosnia Herzegovina – Social Sciences Humanities Studies, Philologist Journal Language, Literary Cultural Studies Historical Views. results show that DHS journal follows official Scopus guidelines, which...

Discovery of association rules from large databases of item sets is an important data mining problem. Association rules are usually stored in relational databases for future use in decision support systems. In this paper, the problem of association rules retrieval and item sets retrieval is recognized as the subset search problem in relational databases. The subset search is not well supported ...

A new, fully automated approach for indexing documents is presented based on associating textwords in a training set of bibliographic citations with the indexing of journals. This journal-level indexing is in the form of a consistent, timely set of journal descriptors (JDs) indexing the individual journals themselves. This indexing is maintained in journal records in a serials authority databas...

Database cracking has been an area of active research in recent years. The core idea of database cracking is to create indexes adaptively and incrementally as a side-product of query processing. Several works have proposed different cracking techniques for different aspects including updates, tuple-reconstruction, convergence, concurrency-control, and robustness. However, there is a lack of any...