Affinity propagation constitutes an exemplar based clustering technique which reliably optimizes the quantization error given a matrix of pairwise data dissimilarities by means of the max-sum algorithm for factor graphs. Albeit very efficient for sparse matrices, it displays squared complexity in the worst case, hence it is not suited as high throughput method due to time and memory constraints...

Facility location (FL) is a well-researched problem in operational-research (Şahin Güvenç & Haldun, 2007), and is closely related to EBC. Given a set of N customers and M potential facilities to open, as well as costs sij for customer i to use facility j, and a facility setup cost cj associated with opening a facility j, we wish to find the set of facilities to open, as well as the assignments ...

Classical techniques for clustering, such as k-means clustering, are very sensitive to the initial set of data centers, so it need to be rerun many times in order to obtain an optimal result. A relatively new clustering approach named Affinity Propagation (AP) has been devised to resolve these problems. Although AP seems to be very powerful it still has several issues that need to be improved. ...

Affinity propagation (AP) is a clustering method that can find data centers or clusters by sending messages between pairs of data points. Seed Affinity Propagation is a novel semisupervised text clustering algorithm which is based on AP. AP algorithm couldn’t cope up with part known data direct. Therefore, focusing on this issue a semi-supervised scheme called incremental affinity propagation c...

Due to the increasing freight volumes passing via seaports checkpoints, and increasingly reported delays in customs clearance procedure, dry port, emerged as one kind of solution to such situation, instead of extending the port scale under limited land use. The place located with dry port (sometimes inland port) can solve not only the congestion embarrassment faced by connected seaport, but als...

Vacation rental websites such as Airbnb have become increasingly popular where rentals are typically short-term and travels or vacations related. Reasonable rental prices play a crucial role in improving user experiences and engagements in these websites. However, the unique properties of their rentals challenge traditional house rentals that are often long-term and study or work related. There...

Based on the current studies on the algorithms of the affinity propagation and normalized cut, a new scalable graph clustering method called APANC (Affinity Propagation And Normalized Cut) is proposed in this paper. During the APANC process, we firstly use the “Affinity Propagation” (AP) to preliminarily group the original data in order to reduce the data-scale, and then we further group the re...

For high dimensional data, the redundant attributes of samplers will not only increase the complexity of the calculation, but also affect the accuracy of final result. The existing attribute reduction methods are encountering bottleneck problem of timeliness and spatiality. In order to looking for a relatively coarse attributes granularity of problem solving, this paper proposes an efficient at...