Digitization and the large-scale preservation of digitized content have engendered new ways of accessing and analyzing collections concurrent with other data mining and extraction efforts. Distant reading refers to the analysis of entire collections instead of close reading individual items like a single physical book or electronic document. The steps performed in distant reading are often common across various types of data collections like books, journals, or web archives, sources that are very valuable and have often been neglected as Big Data. We have extended our tool ArchiveSpark, originally designed to efficiently process Web archives, in order to support arbitrary data collections being served from either local or remote data sources by using metadata proxies. The ability to share and reuse researcher workflows across disciplines with very different datasets makes ArchiveSpark a universal distant reading framework. In this paper, we describe ArchiveSpark's design extensions along an example of how it can be leveraged to analyze symptoms of Polio mentioned in journals from the Medical Heritage Library. Our experiments demonstrate how users can reuse large portions of their job pipeline to accomplish a specific task across diverse data types and sources. Migrating an ArchiveSpark job to process a different dataset introduces an additional average code complexity of only 4.8%. Its expressiveness, scalability, extensibility, reusability, and efficiency has the potential to advance novel and rich methods of scholarly inquiry.

Standard ad hoc routing protocols do not work in intermittently connected networks since end-to-end paths may not exist in such networks. A store-and-forward approach (K. Fall, 2003) has been proposed for such networks. The nodes in such networks move around. Thus, the proposed delay tolerant network (DTN) architecture (K. Fall, 2003) needs to be enhanced with a mobility management scheme to ensure that nodes that wish to correspond with mobile hosts have a way of determining their whereabouts. The mobile hosts may move a short distance and hence remain within the vicinity of a DTN name registrar (DNR) (one communication link away) or they may move far away (multiple communication links away). In this paper, we present the mobility management scheme we propose for DTN environments. In addition, we provide simple analytical formulae to evaluate the latency required for performing location updates, and the useful utilization that each node can use for data transfer assuming that the communication links between nodes are periodically available for a short period of time. Our simple analytical model allows us to draw insights into the impact of near/far movements on the useful utilization

Web spam is behavior that attempts to deceive search engine ranking algorithms. TrustRank is a recent algorithm that can combat web spam. However, TrustRank is vulnerable in the sense that the seed set used by TrustRank may not be sufficiently representative to cover well the different topics on the Web. Also, for a given seed set, TrustRank has a bias towards larger communities. We propose the use of topical information to partition the seed set and calculate trust scores for each topic separately to address the above issues. A combination of these trust scores for a page is used to determine its ranking. Experimental results on two large datasets show that our Topical TrustRank has a better performance than TrustRank in demoting spam sites or pages. Compared to TrustRank, our best technique can decrease spam from the top ranked sites by as much as 43.1%.