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<!--
	This ontology document is licensed under the Creative Commons
	Attribution License. To view a copy of this license, visit
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 <channel rdf:about="http://ebiquity.umbc.edu//tags/html/?t=spam">
  <cc:license rdf:resource="http://creativecommons.org/licenses/by/2.0/" />
  <title><![CDATA[UMBC ebiquity RSS Tag Search]]></title>
  <link><![CDATA[http://ebiquity.umbc.edu//tags/html/?t=spam]]></link>
  <description><![CDATA[UMBC ebiquity RSS Tag Search for spam]]></description>
  <items>
    <rdf:Seq>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/296/Adversarial-Classification-An-Ensemble-based-approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/247/Communities-in-Social-Media-An-Eyepiece-into-Context-User-Intention-and-Influence"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/213/Detecting-spam-blogs-beta-"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/158/The-Multi-Relational-Blogosphere-Empirical-Characterization-and-Spam-Protection"/>
      <rdf:li resource="http://ebiquity.umbc.edu/event/html/id/144/Modeling-the-Spread-of-Influence-on-the-Blogosphere"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/38/Looking-back-at-the-ebiquity-research-group-s-2006"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/37/UMBC-researchers-investigate-the-Blogosphere"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/35/Swoogle-2006-released"/>
      <rdf:li resource="http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere"/>
      <rdf:li resource="http://ebiquity.umbc.edu/project/html/id/68/memeta"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/838/DAbR-Dynamic-Attribute-based-Reputation-scoring-for-Malicious-IP-Address-Detection"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/725/Detecting-Botnets-Using-a-Collaborative-Situational-aware-IDPS"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/461/Ensembles-in-Adversarial-Classification-for-Spam"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/371/The-Information-ecology-of-social-media-and-online-communities"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/408/Spings-und-Splog"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/373/Detecting-Spam-Blogs-An-Adaptive-Online-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/374/Web-2-0-Mining-Analyzing-Social-Media"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/342/Towards-Spam-Detection-at-Ping-Servers"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/362/Spam-in-Blogs-and-Social-Media-Tutorial"/>
      <rdf:li resource="http://ebiquity.umbc.edu/paper/html/id/355/Spam-Blogs-Ping-Servers-and-Adversaries"/>
      <rdf:li resource="http://ebiquity.umbc.edu/research/area/id/27/Social-media"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/227/On-Leveraging-Social-Media"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/216/Spam-in-Blogs-and-Social-Media"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/241/spam-in-blogs-and-social-media"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/212/Splog-Blog-Dataset"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/210/TREC-Blog-Open-Task-Spam-Blog-Detection"/>
      <rdf:li resource="http://ebiquity.umbc.edu/resource/html/id/211/TREC-Blog-Open-Task-Spam-Blog-Detection"/>
    </rdf:Seq>
  </items>
 </channel>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse">
  <title><![CDATA[Analytics for Detecting Web and Social Media Abuse]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/431/Analytics-for-Detecting-Web-and-Social-Media-Abuse</link>
  <description><![CDATA[The Web and online social media provide invaluable communication services to a global Internet user base. The tremendous success of these services, however, has also created valuable opportunities for criminals and other miscreants to abuse them for their own gain. As a result, it is both an important yet challenging problem to detect, monitor, and curtail this abuse. However, the large scale and diversity of these services, combined with the tactics used by attackers, make it difficult to di...]]></description>
  <dc:date>2012-03-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction">
  <title><![CDATA[Cost-Sensitive Information Acquisition for Prediction]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/342/Cost-Sensitive-Information-Acquisition-for-Prediction</link>
  <description><![CDATA[Machine learning systems have been increasingly used in our day-to-day
activities now. Just a few examples include handwritten character
recognition systems, product recommendation systems, face detection
features of cameras, speech recognition in hands-free devices, document
ranking by search engines, fraudulent activity detection for credit card
transactions, spam detection, and medical diagnosis. A critical
component of a machine learning system is the "information" needed to
develo...]]></description>
  <dc:date>2010-04-21</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/296/Adversarial-Classification-An-Ensemble-based-approach">
  <title><![CDATA[Adversarial Classification: An Ensemble-based approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/296/Adversarial-Classification-An-Ensemble-based-approach</link>
  <description><![CDATA[Master's Thesis Defense Announcement

Spam has been studied and dealt with extensively in the email, web, and, recently, blog domains. Recent work has addressed the problem of non-stationarity of the data using ensemble-based approaches. Adversarial classification has been handled by retraining base classifiers using labeled samples obtained from the ensemble. However, frequent retraining is expensive. There is a need is to dynamically determine when the classifiers should be retrained and ...]]></description>
  <dc:date>2009-04-27</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/247/Communities-in-Social-Media-An-Eyepiece-into-Context-User-Intention-and-Influence">
  <title><![CDATA[Communities in Social Media: An Eyepiece into Context, User Intention and Influence]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/247/Communities-in-Social-Media-An-Eyepiece-into-Context-User-Intention-and-Influence</link>
  <description><![CDATA[Communities are central to online social media systems and detecting their structure and membership is critical for many applications. In this talk, I will discuss some of our recent research on both identifying communities and analyzing their content. We leverage the special properties of Social Media data to analyze the communities in an attempt to understand user intentions, context and influence.

 Community detection techniques can be computationally expensive. An approach to reducing ...]]></description>
  <dc:date>2008-06-30</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-">
  <title><![CDATA[Detecting Spam Blogs: An Adaptive Online Approach]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/212/Detecting-Spam-Blogs-An-Adaptive-Online-Approach-</link>
  <description><![CDATA[Weblogs, or blogs, are an important new way to publish information, engage
in discussions, and form communities on the Internet. Blogs are a global
phenomenon, and with numbers well over 100 million they form the core of
the emerging paradigm of Social Media. While the utility of blogs is
unquestionable, a serious problem now afflicts them, that of spam. Spam
blogs, or splogs are blogs with auto-generated or plagiarized content
with the sole purpose of hosting profitable contextual ads ...]]></description>
  <dc:date>2007-09-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/213/Detecting-spam-blogs-beta-">
  <title><![CDATA[Detecting spam blogs (beta)]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/213/Detecting-spam-blogs-beta-</link>
  <description><![CDATA[In our regular weekly Ebiquity meeting, Pranam Kolari will give us a preview of his dissertation defense presentation.  He will greatly appreciate feedback on this pre-release beta version, as long as it doesn't involve suggestions that he do an additional six months of research to confirm and strengthen his experimental results.

See  his defense announcement for the abstract.]]></description>
  <dc:date>2007-09-24</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/158/The-Multi-Relational-Blogosphere-Empirical-Characterization-and-Spam-Protection">
  <title><![CDATA[The Multi-Relational Blogosphere: Empirical Characterization and Spam Protection]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/158/The-Multi-Relational-Blogosphere-Empirical-Characterization-and-Spam-Protection</link>
  <description><![CDATA[Weblogs, or blogs, have become an important new way to publish information,
engage in discussions and form communities. Blogs collectively constitute 
the blogosphere, a highly influential and dynamic subset on the Web. The 
nature of their content and publishing infrastructure requires that they be
modeled, harvested and analyzed differently from the rest of the web.


We first propose a model for the blog graph that extends the more general 
web graph. The web is viewed as a graph G...]]></description>
  <dc:date>2006-05-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/event/html/id/144/Modeling-the-Spread-of-Influence-on-the-Blogosphere">
  <title><![CDATA[Modeling the Spread of Influence on the Blogosphere]]></title>
  <link>http://ebiquity.umbc.edu/event/html/id/144/Modeling-the-Spread-of-Influence-on-the-Blogosphere</link>
  <description><![CDATA[Blogs have become a means by which new ideas and information
spreads rapidly on the web.  They often discuss the latest trends and
echo with reactions on different events in the world.  The collective
wisdom present on the blogosphere is invaluable for market researchers
 and companies launching new products. In this paper, we validate the
effectiveness of some of the influence models on the blogosphere. We
validate the robustness of different heuristics in  presence of splogs
or spam ...]]></description>
  <dc:date>2006-04-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/38/Looking-back-at-the-ebiquity-research-group-s-2006">
  <title><![CDATA[Looking back at the ebiquity research group's 2006]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/38/Looking-back-at-the-ebiquity-research-group-s-2006</link>
  <description><![CDATA[Maybe it's a bit of a cliché, but this is the traditional time to look back on the past year and reflect on how things are going.  It has been an active productive year.  Here's a rundown of our past year by the numbers.

205,000 is the number of visits to the Ebiquity web site.  Our monthly page visits increased five fold over the year and we currently receive about 25,000 visits a month.


   



743 people have
registered as users of the Swoogle
semantic web search system.  By ...]]></description>
  <dc:date>2007-01-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/37/UMBC-researchers-investigate-the-Blogosphere">
  <title><![CDATA[UMBC researchers investigate the Blogosphere]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/37/UMBC-researchers-investigate-the-Blogosphere</link>
  <description><![CDATA[Research on detecting "splogs" by Professors Tim Finin, Anupam Joshi and Tim Oates and PhD students Pranam Kolari and Akshay Java of the Computer Science and Electrical Engineering Department was mentioned in an article in the September issue of Wired Magazine.  Splogs are spam weblogs that are automatically generated to host advertisements or to raise the rank or affiliated web sites.  The UMBC group recently published a study showing that more than half of the active English language blogs ...]]></description>
  <dc:date>2006-09-05</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/35/Swoogle-2006-released">
  <title><![CDATA[Swoogle 2006 released]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/35/Swoogle-2006-released</link>
  <description><![CDATA[Swoogle 2006 is a a major
new version of Swoogle, a search engine for the Semantic Web.
Swoogle helps knowledge engineers and software agents find
knowledge on the web encoded in the semantic web languages RDF
and OWL.  It crawls the Web looking for documents that consists
of RDF or have embedded RDF within them.  USing Swoogle, people
and agents can discover Semantic Web ontologies, terms and data.

 Swoogle 2005 is a nearly complete rewrite of Swoogle Classic, which
now answers to ...]]></description>
  <dc:date>2006-02-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere">
  <title><![CDATA[Welcome to the Splogosphere]]></title>
  <link>http://ebiquity.umbc.edu/getnews/html/id/31/Welcome-to-the-Splogosphere</link>
  <description><![CDATA[Welcome to the Splogosphere!

UMBC study estimates that 75% of posts to English language weblogs are spam


Baltimore, December 16, 2005

 A weblog monitoring system developed by UMBC Ph.D. student Pranam
Kolari shows that a new form of spam -- spam blogs or splogs --
has quickly become a serious problem. 

 Splogs are "fake"
weblog sites that have been set up to carry paid advertisements,
promote affiliated web sites by increasing their PageRank, and to get
new sites noti...]]></description>
  <dc:date>2005-12-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/project/html/id/68/memeta">
  <title><![CDATA[memeta]]></title>
  <link>http://ebiquity.umbc.edu/project/html/id/68/memeta</link>
  <description><![CDATA[Weblogs, or blogs, have become an important new way to publish information, engage in discussions and form communities. The memeta project is developing a framework for representing and studying the structure and content of communities of blogs. We are particularly interested in how metadata about blogs can be extracted, discovered and computed and how that metadata can be used in the analysis of blogs and to provide new blog related services.  Examples of concrete problems we hope to be able...]]></description>
  <dc:date>2005-03-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/838/DAbR-Dynamic-Attribute-based-Reputation-scoring-for-Malicious-IP-Address-Detection">
  <title><![CDATA[DAbR: Dynamic Attribute-based Reputation scoring for Malicious IP Address Detection]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/838/DAbR-Dynamic-Attribute-based-Reputation-scoring-for-Malicious-IP-Address-Detection</link>
  <description><![CDATA[To effectively identify and filter out attacks from known sources like botnets, spammers, virus infected systems etc., organizations increasingly procure services that determine the reputation of IP addresses. Adoption of encryption techniques like TLS 1.2 and 1.3 aggravate this cause, owing to the higher cost of decryption needed for examining traffic contents. Currently, most IP reputation services provide blacklists by analyzing malware and spam records. However, newer but similar IP addre...]]></description>
  <dc:date>2018-11-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/725/Detecting-Botnets-Using-a-Collaborative-Situational-aware-IDPS">
  <title><![CDATA[Detecting Botnets Using a Collaborative Situational-aware IDPS]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/725/Detecting-Botnets-Using-a-Collaborative-Situational-aware-IDPS</link>
  <description><![CDATA[Botnet attacks turn vulnerable victim computers into bots that carry out various malicious activities under a botmaster's control. Some examples of the damage they cause include denial-of-service attacks, click fraud, spamware, and phishing. These attacks can vary in the types of architecture and communication protocols used, which might be modified over the botnet's lifespan. Intrusion detection and prevention systems are one way to safeguard the cyber-physical systems we use, but they have ...]]></description>
  <dc:date>2016-02-19</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/461/Ensembles-in-Adversarial-Classification-for-Spam">
  <title><![CDATA[Ensembles in Adversarial Classification for Spam]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/461/Ensembles-in-Adversarial-Classification-for-Spam</link>
  <description><![CDATA[The standard method for combating spam, either in email or on the web, is to train a classifier on manually labeled instances. As the spammers change their tactics, the performance of such classifiers tends to decrease over time. Gathering and labeling more data to periodically retrain the classifier is expensive. We present a method based on an ensemble of classifiers that can detect when its performance might be degrading and retrain itself, all without manual intervention.  Experiments wit...]]></description>
  <dc:date>2009-11-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/371/The-Information-ecology-of-social-media-and-online-communities">
  <title><![CDATA[The Information ecology of social media and online communities]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/371/The-Information-ecology-of-social-media-and-online-communities</link>
  <description><![CDATA[Social media systems such as weblogs, photo- and link-sharing sites, wikis, and online forums are currently thought to produce up to one-third of new Web content. One thing that sets these ``Web 2.0'' sites apart from traditional Web pages and resources is that they are intertwined with other forms of networked data. Their standard hyperlinks are enriched by social networks, comments, trackbacks, advertisements, tags, RDF data, and metadata.  We describe recent work on building systems that u...]]></description>
  <dc:date>2008-09-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/408/Spings-und-Splog">
  <title><![CDATA[Spings und Splog]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/408/Spings-und-Splog</link>
  <dc:date>2008-05-31</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/373/Detecting-Spam-Blogs-An-Adaptive-Online-Approach">
  <title><![CDATA[Detecting Spam Blogs: An Adaptive Online Approach]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/373/Detecting-Spam-Blogs-An-Adaptive-Online-Approach</link>
  <description><![CDATA[Weblogs, or blogs, are an important new way to publish information, engage in discussions, and form communities on the Internet. Blogs are a global phenomenon, and with numbers well over 100 million they form the core of the emerging paradigm of Social Media. While the utility of blogs is unquestionable, a serious problem now afflicts them, that of spam. Spam blogs, or splogs are blogs with auto-generated or plagiarized content with the sole purpose of hosting profitable contextual ads and/or...]]></description>
  <dc:date>2007-12-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/374/Web-2-0-Mining-Analyzing-Social-Media">
  <title><![CDATA[Web 2.0 Mining: Analyzing Social Media]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/374/Web-2-0-Mining-Analyzing-Social-Media</link>
  <description><![CDATA[Social media systems such as blogs, photo and link
sharing sites, wikis and on-line forums are estimated
to produce up to one third of new Web content. One
thing that sets these ”Web 2.0” sites apart from traditional
Web pages and resources is that they are intertwined
with other forms of networked data. Their standard
hyperlinks are enriched by social networks, comments,
trackbacks, advertisements, tags, RDF data and
metadata. We describe recent work on building systems
that ana...]]></description>
  <dc:date>2007-10-10</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/342/Towards-Spam-Detection-at-Ping-Servers">
  <title><![CDATA[Towards Spam Detection at Ping Servers]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/342/Towards-Spam-Detection-at-Ping-Servers</link>
  <description><![CDATA[Spam blogs, or splogs, are blogs featuring plagiarized or auto-generated content. They create link farms to promote affiliates, and are motivated by the profitability of hosting ads. Splogs infiltrate the blogosphere at ping servers, systems that aggregate blog update pings. Over the past year, our work has focused on detecting and eliminating splogs. As techniques used by spammers have evolved, we have learned how splog signatures are tied to tools that create them, that they are beginning t...]]></description>
  <dc:date>2007-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/362/Spam-in-Blogs-and-Social-Media-Tutorial">
  <title><![CDATA[Spam in Blogs and Social Media, Tutorial]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/362/Spam-in-Blogs-and-Social-Media-Tutorial</link>
  <description><![CDATA[Spam on the Internet dates back over a decade, with its earliest known appearance as an email about the infamous MAKE.MONEY.FAST. campaign. Spam has co-evolved with Internet applications and is now quite common on the World-Wide Web.


As social media systems such as blogs, wikis and bookmark sharing sites have emerged, spammers have quickly developed techniques to infect them as well. The very characteristics underlying the Web, be it version 1.0, 2.0 or 3.0, also enable new varieties o...]]></description>
  <dc:date>2007-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/paper/html/id/355/Spam-Blogs-Ping-Servers-and-Adversaries">
  <title><![CDATA[Spam Blogs: Ping Servers and Adversaries]]></title>
  <link>http://ebiquity.umbc.edu/paper/html/id/355/Spam-Blogs-Ping-Servers-and-Adversaries</link>
  <dc:date>2007-03-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/research/area/id/27/Social-media">
  <title><![CDATA[Social media]]></title>
  <link>http://ebiquity.umbc.edu/research/area/id/27/Social-media</link>
  <description><![CDATA["Social media describes the online technologies and practices that people use to share opinions, insights, experiences, and perspectives. Social media can take many different forms, including text, images, audio, and video. These sites typically use technologies such as blogs, message boards, podcasts, wikis, and vlogs to allow users to interact." (Wikipedia)

The UMBC ebqiuty group as a number of project that involve one or more aspects of social media, inlcuing online games, weblog spam d...]]></description>
  <dc:date>2026-10-08</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach">
  <title><![CDATA[Detecting Spam Blogs: A Machine Learning Approach]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/190/Detecting-Spam-Blogs-A-Machine-Learning-Approach</link>
  <description><![CDATA[Weblogs or blogs are an important new way to publish information, engage in discussions, and form communities on the Internet. The Blogosphere has unfortunately been infected by several varieties of spam-like content. Blog search engines, for example, are inundated by posts from splogs – false blogs with machine generated or hijacked content whose sole purpose is to host ads or raise the PageRank of target sites. We discuss how SVM models based on local and link-based features can be used t...]]></description>
  <dc:date>2006-07-16</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/227/On-Leveraging-Social-Media">
  <title><![CDATA[On Leveraging Social Media]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/227/On-Leveraging-Social-Media</link>
  <dc:date>2007-06-01</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/216/Spam-in-Blogs-and-Social-Media">
  <title><![CDATA[Spam in Blogs and Social Media]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/216/Spam-in-Blogs-and-Social-Media</link>
  <description><![CDATA[Spam on the Internet dates back over a decade, with its earliest known appearance as an email about the infamous MAKE.MONEY.FAST. campaign. Spam has co-evolved with Internet applications and is now quite common on the World-Wide Web.


As social media systems such as blogs, wikis and bookmark sharing sites have emerged, spammers have quickly developed techniques to infect them as well. The very characteristics underlying the Web, be it version 1.0, 2.0 or 3.0, also enable new varieties o...]]></description>
  <dc:date>2007-04-02</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/241/spam-in-blogs-and-social-media">
  <title><![CDATA[spam in blogs and social media]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/241/spam-in-blogs-and-social-media</link>
  <description><![CDATA[Spam on the Internet dates back over a decade, with its earliest known appearance as an email about the infamous MAKE.MONEY.FAST. campaign. Spam has co-evolved with Internet applications and is now quite common on the World-Wide Web.

As social media systems such as blogs, wikis and bookmark sharing sites have emerged, spammers have quickly developed techniques to infect them as well. The very characteristics underlying the Web, be it version 1.0, 2.0 or 3.0, also enable new varieties of sp...]]></description>
  <dc:date>2007-03-25</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/212/Splog-Blog-Dataset">
  <title><![CDATA[Splog Blog Dataset]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/212/Splog-Blog-Dataset</link>
  <description><![CDATA[This dataset consists of 3000 blog homepages, out of which 700 have been labeled as splogs, and another 700 as authentic blogs.


This training set was used in results of three papers, with emphasis on identifying blogs [1], on detecting spam blogs [2], and on analysing the splogosphere [3].


This collection can be used in further experimenting with splogs, or for building filters that could be deployed in real world systems. We, and our academic and industrial collaborators have bee...]]></description>
  <dc:date>2006-11-14</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/210/TREC-Blog-Open-Task-Spam-Blog-Detection">
  <title><![CDATA[TREC Blog Open Task: Spam Blog Detection]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/210/TREC-Blog-Open-Task-Spam-Blog-Detection</link>
  <dc:date>2006-11-12</dc:date>
 </item>
 <item rdf:about="http://ebiquity.umbc.edu/resource/html/id/211/TREC-Blog-Open-Task-Spam-Blog-Detection">
  <title><![CDATA[TREC Blog Open Task: Spam Blog Detection]]></title>
  <link>http://ebiquity.umbc.edu/resource/html/id/211/TREC-Blog-Open-Task-Spam-Blog-Detection</link>
  <dc:date>2006-11-12</dc:date>
 </item>
</rdf:RDF>
