Engineering topics

Gregory, Michelle L

Publications and source records attributed to Gregory, Michelle L.

12 records

DOE OSTI2014

Automatic identification of abstract online groups

Online abstract groups, in which members aren't explicitly connected, can be automatically identified by computer-implemented methods. The methods involve harvesting records from social media and extracting content-based and structure-based features from each record. Each record includes a social-media posting and is associated with one or more entities. Each feature is stored on a data storage device and includes a computer-readable representation of an attribute of one or more records. The methods further involve grouping records into record groups according to the features of each record. Further still the methods involve calculating an n-dimensional surface representing each record group and defining an outlier as a record having feature-based distances measured from every n-dimensional surface that exceed a threshold value. Each of the n-dimensional surfaces is described by a footprint that characterizes the respective record group as an online abstract group.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2012

Identifying Differences in Cultural Behavior in Online Groups

We have developed methods to identify online communities, or groups, using a combination of structural information variables and content information variables from weblog posts and their comments to build a characteristic footprint for groups. We have worked with both explicitly connected groups and 'abstract' groups, in which the connection between individuals is in interest (as determined by content based features) and behavior (metadata based features) as opposed to explicit links. We find that these variables do a good job at identifying groups, placing members within a group, and helping determine the appropriate granularity for group boundaries. The group footprint can then be used to identify differences between the online groups. In the work described here we are interested in determining how an individual's online behavior is influenced by their membership in more than one group. For example, individuals belong to a certain culture; they may belong as well to a demographic group, and other 'chosen' groups such as churches or clubs. There is a plethora of evidence surrounding the culturally sensitive adoption, use, and behavior on the Internet. In this work we begin to investigate how culturally defined internet behaviors may influence behaviors of subgroups. We do this through a series of experiments in which we analyze the interaction between culturally defined behaviors and the behaviors of the subgroups. Our goal is to (a) identify if our features can capture cultural distinctions in internet use, and (b) determine what kinds of interaction there are between levels and types of groups.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

Semantic Features for Classifying Referring Search Terms

When an internet user clicks on a result in a search engine, a request is submitted to the destination web server that includes a referrer field containing the search terms given by the user. Using this information, website owners can analyze the search terms leading to their websites to better understand their visitors needs. This work explores some of the features that can be used for classification-based analysis of such referring search terms. We present initial results for the example task of classifying HTTP requests countries of origin. A system that can accurately predict the country of origin from query text may be a valuable complement to IP lookup methods which are susceptible to the obfuscation of dereferrers or proxies. We suggest that the addition of semantic features improves classifier performance in this example application. We begin by looking at related work and presenting our approach. After describing initial experiments and results, we discuss paths forward for this work.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

IDENTIFYING ON-LINE GROUPS BASED ON CONTENT AND COLLECTIVE BEHAVIORAL PATTERNS

Online communities, or groups, have largely been defined based on links, page rank, and eigenvalues. In this paper we explore identifying abstract groups, groups where member's interests and online footprints are similar but they are not necessarily connected to one another explicitly. We use a combination of structural information and content information from posts and their comments to build a footprint for groups. We find that these variables do a good job at identifying groups, placing members within a group, and help determine the appropriate granularity for group boundaries.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

Hypothesis analysis methods, hypothesis analysis devices, and articles of manufacture

Hypothesis analysis methods, hypothesis analysis devices, and articles of manufacture are described according to some aspects. In one aspect, a hypothesis analysis method includes providing a hypothesis, providing an indicator which at least one of supports and refutes the hypothesis, using the indicator, associating evidence with the hypothesis, weighting the association of the evidence with the hypothesis, and using the weighting, providing information regarding the accuracy of the hypothesis.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2011

Methods of defining ontologies, word disambiguation methods, computer systems, and articles of manufacture

Methods of defining ontologies, word disambiguation methods, computer systems, and articles of manufacture are described according to some aspects. In one aspect, a word disambiguation method includes accessing textual content to be disambiguated, wherein the textual content comprises a plurality of words individually comprising a plurality of word senses, for an individual word of the textual content, identifying one of the word senses of the word as indicative of the meaning of the word in the textual content, for the individual word, selecting one of a plurality of event classes of a lexical database ontology using the identified word sense of the individual word, and for the individual word, associating the selected one of the event classes with the textual content to provide disambiguation of a meaning of the individual word in the textual content.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2011

Automatically Identifying Groups Based on Content and Collective Behavioral Patterns of Group Members

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

Lexicon generation methods, lexicon generation devices, and lexicon generation articles of manufacture

Lexicon generation methods, computer implemented lexicon editing methods, lexicon generation devices, lexicon editors, and articles of manufacture are described according to some aspects. In one aspect, a lexicon generation method includes providing a seed vector indicative of occurrences of a plurality of seed terms within a plurality of text items, providing a plurality of content vectors indicative of occurrences of respective ones of a plurality of content terms within the text items, comparing individual ones of the content vectors with respect to the seed vector, and responsive to the comparing, selecting at least one of the content terms as a term of a lexicon usable in sentiment analysis of text.

Carter, Richard J↗

DOE OSTI2010

Quantifying Sentiment and Influence in Blogspaces

The weblog, or blog, has become a popular form of social media, through which authors can write posts, which can in turn generate feedback in the form of user comments. When considered in totality, a collection of blogs can thus be viewed as a sort of informal collection of mass sentiment and opinion. An obvious topic of interest might be to mine this collection to obtain some gauge of public sentiment over the wide variety of topics contained therein. However, the sheer size of the so-called blogosphere, combined with the fact that the subjects of posts can vary over a practically limitless number of topics poses some serious challenges when any meaningful analysis is attempted. Namely, the fact that largely anyone with access to the Internet can author their own blog, raises the serious issue of credibility— should some blogs be considered to be more influential than others, and consequently, when gauging sentiment with respect to a topic, should some blogs be weighted more heavily than others? In addition, as new posts and comments can be made on almost a constant basis, any blog analysis algorithm must be able to handle such updates efficiently. In this paper, we give a formalization of the blog model. We give formal methods of quantifying sentiment and influence with respect to a hierarchy of topics, with the specific aim of facilitating the computation of a per-topic, influence-weighted sentiment measure. Finally, as efficiency is a specific endgoal, we give upper bounds on the time required to update these values with new posts, showing that our analysis and algorithms are scalable.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

Social Media and Social Reality - Theory, Evidence and Validation

Social Media provide an exciting and novel view into social phenomena. The vast amounts of data that can be gathered from the Internet coupled with massively parallel supercomputers such as the Cray XMT open new vistas for research. Conclusions drawn from such analysis must recognize that social media are distinct from the underlying social reality. Rigorous validation is essential. This paper briefly presents results obtained from computational analysis of social media - utilizing both blog and twitter data. Validation of these results is discussed in the context of a framework of established methodologies from the social sciences. Finally, an outline for a set of supporting studies is proposed.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

Towards Efficient Collaboration in Cyber Security

Cyber security analysts in different geographical and organizational domains are often largely tasked with similar duties, albeit with domain-specific variations. These analysts necessarily perform much of the same work independently— for instance, analyzing the same list of security bulletins released by largely the same set of software vendors. As such, communication and collaboration between such analysts would be mutually beneficial to the analysts involved, potentially reducing redundancy and offering the opportunity to preemptively alert each other to high-severity security alerts in a more timely fashion. However, several barriers to practical and efficient collaboration exist, and as such, no such framework exists to support such efforts. In this paper, we discuss the inherent difficulties which make efficient collaboration between cyber security analysts a difficult goal to achieve. We discuss preliminary ideas and concepts towards a collaborative cyber-security framework currently under development, whose goal is to facilitate analyst collaboration across these boundaries. While still in its early stages, we describe work-in-progress towards achieving this goal, including motivation, functionality, concepts, and a high-level description of the proposed system architecture.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2010

Collaborative Knowledge Discovery & Marshalling for Intelligence & Security Applications

This paper discusses the Knowledge Encapsulation Framework, a flexible, extensible evidence-marshalling environment built upon a natural language processing pipeline and exposed to users via an open-source semantic wiki. We focus our discussion on applications of the framework to intelligence and security applications, specifically, an instantiation of the KEF environment for researching illicit trafficking in nuclear materials.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗