Fine Grained Approach for Domain Specific Seed URL Extraction

Domain Specific Search Engines are expected to provide relevant search results. Availability of enormous number of URLs across subdomains improves relevance of domain specific search engines. The current methods for seed URLs can be systematic ensuring representation of subdomains. We propose a fine grained approach for automatic extraction of seed URLs at subdomain level using Wikipedia and Twitter as repositories. A SeedRel metric and a Diversity Index for seed URL relevance are proposed to measure subdomain coverage. We implemented our approach for \u27Security - Information and Cyber\u27 domain and identified 34,007 Seed URLs and 400,726 URLs across subdomains. The measured Diversity index value of 2.10 conforms that all subdomains are represented, hence, a relevant \u27Security Search Engine\u27 can be built. Our approach also extracted more URLs (seed and child) as compared to existing approaches for URL extraction

Bootstrapping Web Archive Collections From Micro-Collections in Social Media

In a Web plagued by disappearing resources, Web archive collections provide a valuable means of preserving Web resources important to the study of past events. These archived collections start with seed URIs (Uniform Resource Identifiers) hand-selected by curators. Curators produce high quality seeds by removing non-relevant URIs and adding URIs from credible and authoritative sources, but this ability comes at a cost: it is time consuming to collect these seeds. The result of this is a shortage of curators, a lack of Web archive collections for various important news events, and a need for an automatic system for generating seeds. We investigate the problem of generating seed URIs automatically, and explore the state of the art in collection building and seed selection. Attempts toward generating seeds automatically have mostly relied on scraping Web or social media Search Engine Result Pages (SERPs). In this work, we introduce a novel source for generating seeds from URIs in the threaded conversations of social media posts created by single or multiple users. Users on social media sites routinely create and share narratives about news events consisting of hand-selected URIs of news stories, tweets, videos, etc. In this work, we call these posts Micro-collections, whether shared on Reddit or Twitter, and we consider them as an important source for seeds. This is because, the effort taken to create Micro-collections is an indication of editorial activity and a demonstration of domain expertise. Therefore, we propose a model for generating seeds from Micro-collections. We begin by introducing a simple vocabulary, called post class for describing social media posts across different platforms, and extract seeds from the Micro-collections post class. We further propose Quality Proxies for seeds by extending the idea of collection comparison to evaluation, and present our Micro-collection/Quality Proxy (MCQP) framework for bootstrapping Web archive collections from Micro-collections in social media