Data Mining Practical Machine Learning Tools and Techniques

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing.We have crawled the entire Twitter site and obtained 41.7 million user profiles, 1.47 billion social relations, 4,262 trending topics, and 106 million tweets. In its follower-following topology analysis we have found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks [28]. In order to identify influentials on Twitter, we have ranked users by the number of followers and by PageRank and found two rankings to be similar. Ranking by retweets differs from the previous two rankings, indicating a gap in influence inferred from the number of followers and that from the popularity of one's tweets. We have analyzed the tweets of top trending topics and reported on their temporal behavior and user participation. We have classified the trending topics based on the active period and the tweets and show that the majority (over 85%) of topics are headline news or persistent news in nature. A closer look at retweets reveals that any retweeted tweet is to reach an average of 1,000 users no matter what the number of followers is of the original tweet. Once retweeted, a tweet gets retweeted almost instantly on next hops, signifying fast diffusion of information after the 1st retweet.To the best of our knowledge this work is the first quantitative study on the entire Twittersphere and information diffusion on it.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=7104&context=sis_research

What is Twitter, a social network or a news media?

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

/pdf/linked-data-the-story-so-far-2a9zvmaysa.pdf

Linked Data - the story so far

Obesity now affects one in five children in the United States. Discrimination against overweight children begins early in childhood and becomes progressively institutionalized. Because obese children tend to be taller than their nonoverweight peers, they are apt to be viewed as more mature. The inappropriate expectations that result may have an adverse effect on their socialization. Many of the cardiovascular consequences that characterize adult-onset obesity are preceded by abnormalities that begin in childhood. Hyperlipidemia, hypertension, and abnormal glucose tolerance occur with increased frequency in obese children and adolescents. The relationship of cardiovascular risk factors to visceral fat independent of total body fat remains unclear. Sleep apnea, pseudotumor cerebri, and Blount's disease represent major sources of morbidity for which rapid and sustained weight reduction is essential. Although several periods of increased risk appear in childhood, it is not clear whether obesity with onset early in childhood carries a greater risk of adult morbidity and mortality. Obesity is now the most prevalent nutritional disease of children and adolescents in the United States. Although obesity-associated morbidities occur more frequently in adults, significant consequences of obesity as well as the antecedents of adult disease occur in obese children and adolescents. In this review, I consider the adverse effects of obesity in children and adolescents and attempt to outline areas for future research. I refer to obesity as a body mass index greater than the 95th percentile for children of the same age and gender.

Health Consequences of Obesity in Youth: Childhood Predictors of Adult Disease

Report on the 2nd Workshop on the Open Archives Initiative, Gaining Independence with e-Print Archives and OAI: 17 - 19 October 2002, CERN, Switzerland.

Time-evolving graphs represent a set of individuals (nodes) and their edges (relationships) over time. How these graphs are represented in data structures determines what information is easy to obtain from them. Now that we have such massive social networks with dynamic lifetimes, even basic data structures are too large to fit into main memory. Clearly, this poses a problem to areas such as time-evolving graph pattern analysis. Therefore, it is an interesting field of study to design time-evolving graph compressions that can efficiently answer certain queries about the graph at any given point in time.If a single snapshot of a graph at a moment in time can be considered a 2D matrix, then can we visualize these time-evolving graphs as 3D matrices and then use a novel technique to compress the entire graph over time. Our technique is based on our previous work using compressed binary trees. In this work, we adapt our strategy to compress time-evolving graphs, rather than static ones. We manage to maintain our minimal main memory overhead by not requiring an intermediate structure (e.g. adjacency list) to compress. This compression is queryable, meaning that the data can be read without decompression. It is also streaming, meaning that the data can be changed without decompression. This includes adding/removing edges in individual frames. We test our algorithms on public, anonymized, massive, time-evolving graphs such as Flickr, Yahoo!, and Wikipedia. Our empirical evaluation is based on several parameters including time to compress, size of compressed graph, and time to execute queries. Our compression rates are highly competitive, as we achieve the smallest representation of 4.9GB on our largest dataset which only spans three days yet occupies 21.5GB of space.

Queryable Compression on Time-Evolving Social Networks with Streaming

Web annotation has been receiving increased attention recently with the organization of the Open Annotation Collaboration and new tools for open annotation, such as Hypothes.is. In this paper, we investigate the prevalence of orphaned annotations, where a live Web page no longer contains the text that had previously been annotated in the Hypothes.is annotation system (containing 6281 highlighted text annotations). We found that about 27 % of highlighted text annotations can no longer be attached to their live Web pages. Unfortunately, only about 3.5 % of these orphaned annotations can be reattached using the holdings of current public web archives. For those annotations that are still attached, 61 % are in danger of becoming orphans if the live Web page changes. This points to the need for archiving the target of annotations at the time the annotation is created.

/pdf/quantifying-orphaned-annotations-in-hypothes-is-5bz14bfs6x.pdf

Quantifying Orphaned Annotations in Hypothes.is

Although the Internet Archive's Wayback Machine is the largest and most well-known web archive, there have been a number of public web archives that have emerged in the last several years. With varying resources, audiences and collection development policies, these archives have varying levels of overlap with each other. While individual archives can be measured in terms of number of URIs, number of copies per URI, and intersection with other archives, to date there has been no answer to the question "How much of the Web is archived?" We study the question by approximating the Web using sample URIs from DMOZ, Delicious, Bitly, and search engine indexes; and, counting the number of copies of the sample URIs exist in various public web archives. Each sample set provides its own bias. The results from our sample sets indicate that range from 35%-90% of the Web has at least one archived copy, 17%-49% has between 2-5 copies, 1%-8% has 6-10 copies, and 8%-63% has more than 10 copies in public web archives. The number of URI copies varies as a function of time, but no more than 31.3% of URIs are archived more than once per month.

How Much of the Web Is Archived

For traditional library collections, archivists can select a representative sample from a collection and display it in a featured physical or digital library space. Web archive collections may consist of thousands of archived pages, or mementos. How should an archivist display this sample to drive visitors to their collection? Search engines and social media platforms often represent web pages as cards consisting of text snippets, titles, and images. Web storytelling is a popular method for grouping these cards in order to summarize a topic. Unfortunately, social media platforms are not archive-aware and fail to consistently create a good experience for mementos. They also allow no UI alterations for their cards. Thus, we created MementoEmbed to generate cards for individual mementos and Raintale for creating entire stories that archivists can export to a variety of formats.

/pdf/mementoembed-and-raintale-for-web-archive-storytelling-2amimw8bhz.pdf

Michael L. Nelson

Papers

Report on the 2nd Workshop on the Open Archives Initiative, Gaining Independence with e-Print Archives and OAI: 17 - 19 October 2002, CERN, Switzerland.

Queryable Compression on Time-Evolving Social Networks with Streaming

Quantifying Orphaned Annotations in Hypothes.is

How Much of the Web Is Archived

MementoEmbed and Raintale for Web Archive Storytelling