ELM (Extreme Learning Machine) is a single hidden layer feed-forward network, where the weights between input and hidden layer are initialized randomly. ELM is efficient due to its utilization of the analytical approach to compute weights between hidden and output layer. However, ELM still fails to output the semantic classification outcome. To address such limitation, in this paper, we propose...

Top-k queries are useful in retrieving top-k records from a given set of records depending on the value of a function F on their attributes. Many techniques have been proposed in database literature for answering top-k queries. These are mainly categorized into three: Sorted-list based, layer based and View based. In first category, records are sorted along each dimension and then assigned a ra...

A large-scale wireless sensor networks (WSNs) can be deployed for top-k querying applications. There are many top-k querying algorithms which are based on traditional routing approaches. In this article, we proposed a clustering-based routing for top-k querying (CRTQ) in WSNs to save the energy consumption and extend the network lifetime. The proposed scheme consists of two parts: one is the cl...

Top-k spatial preference queries rank objects based on the score of feature objects in their spatial neighborhood. Top-k preference queries are crucial for a wide range of location based services such as hotel browsing and apartment searching. In recent years, a lot of research has been conducted on processing of top-k spatial preference queries in Euclidean space. While few algorithms study to...

Crowdsourced top-k computation has attracted significant attention recently, thanks to emerging crowdsourcing platforms, e.g., Amazon Mechanical Turk and CrowdFlower. Crowdsourced top-k algorithms ask the crowd to compare the objects and infer the top-k objects based on the crowdsourced comparison results. The crowd may return incorrect answers, but traditional top-k algorithms cannot tolerate ...

We consider a distributed system where each node has a local count for each item (similar to elections where nodes are ballot boxes and items are candidates). A top-k query in such a system asks which are the k items whose sum of counts, across all nodes in the system, is the largest. In this paper we present a Monte-Carlo algorithm that outputs, with high probability, a set of k candidates whi...

We consider a distributed system where each node keeps a local count for items (similar to elections where nodes are ballots and items are candidates). A top-k query in such a system asks which are the k items whose global count, across all nodes in the system, is the largest. This thesis presents a Monte-Carlo algorithm that outputs, with high probability, a set of k candidates which approxima...

We study an important data analysis operator, which extracts the k most important groups from data (i.e., the k groups with the highest aggregate values). In a data warehousing context, an example of the above query is “find the 10 combinations of product-type and month with the largest sum of sales”. The problem is challenging as the potential number of groups can be much larger than the memor...

Penelitian ini mengekstrak pola pergerakan harga saham saat pandemi COVID-19 berdasarkan aturan asosiasi dan banyaknya teratas k, yang disebut juga top-k. Untuk menambang top-k, penelitian menggunakan Top-K Association Rules Mining algorithm. Tujuan dari adalah untuk memberikan rekomendasi mudah dipahami dengan menunjukkan korelasi antara COVID-19. Oleh karena itu, berfokus mendefinisikan tipe ...

The problem of finding the k most critical nodes, referred to as the top-k problem, is a very important one in several contexts such as information diffusion and preference aggregation in social networks, clustering of data points, etc. It has been observed in the literature that the value allotted to a node by most of the popular cooperative game theoretic solution concepts, acts as a good mea...