Related papers: BUbiNG: Massive Crawling for the Masses
Modern social networks have become sources for vast quantities of data. Having access to such big data can be very useful for various researchers and data scientists. In this paper we describe Loklak, an open source distributed peer to peer…
World Wide Web consists of more than 50 billion pages online. It is highly dynamic i.e. the web continuously introduces new capabilities and attracts many people. Due to this explosion in size, the effective information retrieval system or…
With the ever proliferating size and scale of the WWW [1] efficient ways of exploring content are of increasing importance. How can we efficiently retrieve information from it through crawling? And in this era of tera and multi-core…
Journalistic fact-checking, as well as social or economic research, require analyzing high-quality statistics datasets (SDs, in short). However, retrieving SD corpora at scale may be hard, inefficient, or impossible, depending on how they…
Motivation: In this paper we present the latest release of EBIC, a next-generation biclustering algorithm for mining genetic data. The major contribution of this paper is adding support for big data, making it possible to efficiently run…
We present new system architecture, a distributed framework designed to support pervasive computing applications. We propose a new architecture consisting of a search engine and peripheral clients that addresses issues in scalability, data…
Today World Wide Web (WWW) has become a huge ocean of information and it is growing in size everyday. Downloading even a fraction of this mammoth data is like sailing through a huge ocean and it is a challenging task indeed. In order to…
Automated debugging, long pursued in a variety of fields from software engineering to cybersecurity, requires a framework that offers the building blocks for a programmable debugging workflow. However, existing debuggers are primarily…
This paper proposes a novel model for web crawling suitable for large-scale web data acquisition. This model first divides web data into several sub-data, with each sub-data corresponding to a thread task. In each thread task, web crawling…
At present, the de-facto standard for providing contents in the Internet is the World Wide Web. A technology, which is now emerging on the Web, is Content-Based Image Retrieval (CBIR). CBIR applies methods and algorithms from computer…
The widespread development and adoption of open-source software have built an ecosystem for open development and collaboration. In this ecosystem, individuals and organizations collaborate to create high-quality software that can be used by…
Public information contains valuable Cyber Threat Intelligence (CTI) that is used to prevent future attacks. While standards exist for sharing this information, much appears in non-standardized news articles or blogs. Monitoring online…
In this paper, we introduce a web-scale general visual search system deployed in Microsoft Bing. The system accommodates tens of billions of images in the index, with thousands of features for each image, and can respond in less than 200…
Nowadays, the size of the Internet is experiencing rapid growth. As of December 2014, the number of global Internet websites has more than 1 billion and all kinds of information resources are integrated together on the Internet, however,the…
Censorship of the Internet is widespread around the world. As access to the web becomes increasingly ubiquitous, filtering of this resource becomes more pervasive. Transparency about specific content that citizens are denied access to is…
Biclustering is a two way clustering approach involving simultaneous clustering along two dimensions of the data matrix. Finding biclusters of web objects (i.e. web users and web pages) is an emerging topic in the context of web usage…
Bug Localization is the process of locating potential error-prone files or methods from a given bug report and source code. There is extensive research on bug localization in the literature that focuses on applying information retrieval…
Biclustering is a data mining technique which searches for local patterns in numeric tabular data with main application in bioinformatics. This technique has shown promise in multiple areas, including development of biomarkers for cancer,…
Web crawlers visit internet applications, collect data, and learn about new web pages from visited pages. Web crawlers have a long and interesting history. Early web crawlers collected statistics about the web. In addition to collecting…
Modern web scraping struggles with dynamic, interactive websites that require more than static HTML parsing. Current methods are often brittle and require manual customization for each site. To address this, we introduce Webscraper, a…