The more Chinese language materials come out, the more we have to focus on the “same personal name” problem. In our personal name disambiguation system, the hierarchical agglomerative clustering is applied, and named entity is used as feature for document similarity calculation. We propose a two-stage strategy in which the first stage involves word segmentation and named entity recognition (NER...

In this paper two new heuristics, named Min–min-C and Max–min-C, are proposed able to provide nearoptimal solutions to themapping of parallel applications, modeled as Task Interaction Graphs, on computational clouds. The aim of these heuristics is to determine mapping solutions which allow exploiting at best the available cloud resources to execute such applications concurrentlywith the other c...

Spectral clustering, while perhaps the most efficient heuristics for graph partitioning, has recently gathered bad reputation for failure over large-scale power law graphs. In this chapter we identify the abundance of small-size communities connected by long tentacles as the major obstacle for spectral clustering. These subgraphs hide the higher level structure and result in a highly degenerate...

Scaling conformant planning is a problem that has received much attention of late. Many planners solve the problem as a search in the space of belief states, and some heuristic guidance techniques have been developed to estimate the distance between belief states. We claim that heuristic techniques in the past involved an ad hoc combination of classical planning heuristics and cardinality measu...

Recognition of Named Entities (NEs) is a difficult process in Indian languages like Hindi, Telugu, etc., where sufficient gazetteers and annotated corpora are not available compared to English language. This paper details a novel clustering and co-occurrence based approach to map English NEs with their equivalent representations from different languages recognized in a language-independent way....

Blockchain analysis is essential for understanding how cryptocurrencies like Bitcoin are used in practice, and address clustering a cornerstone of blockchain analysis. However, current techniques rely on heuristics that have not been rigorously evaluated or optimized. In this paper, we tackle several challenges change identification clustering. First, build ground truth set transactions with kn...

This paper presents a new mathematical model, in which the location of hubs is fixed and their capacity is determined based on facilities and factories allocated to it. In order to feed the client's nodes, different types of vehicles of different capacities are considered, in which the clients are allocated to hubs, and types and numbers of vehicles are allocated to the factory's facilities. To...

Morphological image segmentation is an essential tool for various image analysis tasks. In this paper, we propose two successive region-merging algorithms that mainly aim to represent homogeneous objects simply and clearly. First, we define a marker cluster and extract markers having similar intensity values from each marker cluster. After initial segmentation using the markers, perceptually in...

It is difficult to follow the entirity of the global of news sources , and the events happening everyday. If an analyst in her area has to follow and map all these according to the timeline they happen, the task quickly becomes overwhelming. We present an online tool which attempts to ease the analyst’s task of finding all news articles about an event, and sorting and mapping them on a timeline...