As online job boards have grown crowded amid the recession, many big companies, including Microsoft Corp., Verizon Communications Inc., Raytheon Corp. and Viacom Inc.'s MTV Networks, now list job openings on the Twitter microblogging site.

Jon Protas/The Wall Street Journal

Twitter lets job seeksers follow feeds that list jobs from a variety of companies.

For employers, Twitter—where users post updates, or "tweets," of no more than 140 characters—offers one more way to find and attract candidates, and a cheaper alternative to big online job boards. It also helps companies target social-media-savvy job hunters and convey an innovative image. For job seekers, Twitter offers the chance to interact one-on-one with companies' recruiters and can be more convenient than job boards.

Job hunters can sign up to follow a company's listings on Twitter or receive tweets about jobs through a third-party service. They usually need to click a link in the tweet to access the listing online, where they can submit their résumé or application. They can also reply to the tweet with a question or comment; sometimes, employers tweet back.

With so many people looking for jobs now, some employers say they like that Twitter yields just enough job leads—but not too many. Job boards have "become saturated," says Mike Rickheim, vice president of global talent acquisition for Newell Rubbermaid Inc., a global manufacturer based in Atlanta.

"With Twitter, we don't have to go through that huge pile of résumés." Mr. Rickheim says the company uses Twitter to fill positions that tend to attract tons of applicants on job boards, such as administrative roles, as well as to share company news.

(Of course, recruiters note, the more popular Twitter gets, the more applicants it will likely attract.)

People who respond to job tweets typically have social-media skills, and some employers say they use the service to target them. In March, MediaSource Inc., a video-production and publicity firm in Columbus, Ohio, advertised a media-relations specialist job only on Twitter, LinkedIn and two niche job boards, says Lisa Arledge Powell, MediaSource's president.

"We needed someone that understood social media, so we thought, 'Why not go to where these people go?' " she says.

Andrea Slesinski, who was following the company's Twitter feed, saw the job listing and quickly tweeted her interest. She got an interview request within a week and was hired.

Image is a big part of Twitter's appeal to employers, as using it to engage with job seekers can suggest they're cutting-edge. "Verizon is a technology company so we need to be out there," says Asif Zulfiqar, a talent-management specialist at the New York-based telecommunications firm, which began listing jobs on Twitter in March.

But the image issue cuts both ways, he notes, and job seekers don't always pay enough attention to how they appear to employers on Twitter. Recently a follower of Verizon's jobs feed tweeted to the company something along the lines of, "Hey dude, you got any jobs in California?" says Mr. Zulfiqar.

The writer's casual tone made a poor impression, he says. "I want to see something more professional," he says. "You want to put your best foot forward."

Indeed, people trolling for jobs on Twitter need to tweet with care—not just when they're interacting with employers, says Cynthia Shapiro, a former human-resources executive and career coach in Woodland Hills, Calif. Hiring managers could use information they find on Twitter, just as on Facebook, to form opinions about an applicant's employability. People sometimes disclose personal things over Twitter, like work-family challenges, that an employer couldn't ask about in an interview but which might color their impression if they knew. For example, if an employer sees on Twitter that a candidate is going through a messy divorce, they might "assume you're going to be distracted," Ms. Shapiro says.

Job seekers can do their own sleuthing on Twitter to research prospective employers. In June, Rob Totaro landed an interview for an account-manager job at Potratz Partners Advertising, a small agency in Schenectady, N.Y., after learning about the position on Twitter. In the meeting, he joked that he wasn't sure he could work for a firm that supports the Red Sox, which he had discovered from reading tweets the company posted about a recent employee outing to a ballgame. "It was a great ice breaker," says Mr. Totaro. He got the job.

Twitter users say the service can be more convenient than online job boards, allowing users to follow feeds that list jobs from a variety of companies rather than trolling through thousands of job-board listings. "It's an efficient way to get a general idea of what type of jobs are out there," says Ryan Kellett, a senior at Middlebury College in Middlebury, Vt.

He subscribes to about a half-dozen job feeds on Twitter. "It's a little bit more of a chore to go on [job boards] on a daily basis," he says. "You don't know if there's new content on there."

Twitter's interactivity also can provide a new source of advice for candidates. Subscribers to Google Inc.'s jobs feed, which went live on June 29, can pose employment questions to recruiters at the Mountain View, Calif., company, says a spokeswoman. Recently someone posted a tweet asking what job candidates should wear to interviews at Google.

A little over an hour later, a recruiter tweeted back: "We care more about your mind than your clothes," the spokeswoman says.

Cost is a main draw for employers, many of which post jobs on their own Twitter feeds free. Some services distribute job listings for employers on Twitter for a fee, but they are generally less than the cost of posting on a big job board.

U.K.-based InterContinental Hotels Group PLC, which has U.S. headquarters in Atlanta, began listing jobs on Twitter in July through a distribution service called TweetMyJobs, which charges 99 cents to promote one position for a day. The service also offers volume discounts. Francene Taylor, a talent-acquisition technology manager for InterContinental, says the service is more affordable than most job boards and she expects it to help the hospitality company save money as more job seekers turn to the company's Twitter feed to look for postings.

"We will see a decline in a need to use the major job boards and that will mean we won't have to spend quite as much," she says.

Ms. Taylor says the quality of the candidates, for all positions including room attendant and housekeeper supervisor, is the same as what comes through job boards.

But sometimes, Twitter produces enough leads that InterContinental doesn't need to advertise the jobs elsewhere. During the last week of August, she says, 4,622 people clicked through to the company's job-listings section from Twitter.

Write to Sarah E. Needleman at sarah.needleman@wsj.com

MS Thesis Defense

A Specialist Approach for Classification of Column Data

Nikhil Puranik

1:30pm Friday 24 August, 2012, 325b ITE, UMBC

Much information is encoded in spreadsheets, databases, and tables on the Web and in documents. Interpreting this content and making its meaning explicit in a representation language like RDF enables many applications. This thesis addresses the problem of identifying the semantic type of the information represented in a table column containing conventionally encoded data such as phone numbers or stock ticker symbols. We describe a ‘specialist’ approach for classification in which different specialists work together to come up with a ranked list for the given input column. We use three types of specialists: those based on regular expressions, dictionaries and classifiers. We discuss a serial and parallel framework for the specialists. We evaluate our system in two ways: by testing individual specialist for accuracy and by testing the performance of the overall system in terms of generation of ranked list. We also discuss the scalability of the system in terms of addition of new specialists and performance impact for systems with hundreds of specialists.

Committee: Drs. Tim Finin (chair), Anupam Joshi, Tim Oates and Yelena Yesha

I played cricket for the UMBC 22-Yards team last year, but due to time constraints this year I haven’t been able to play in any matches.

Read more about Zulqarnain's research by visiting the link below...

Ph.D. Dissertation Defense

Joint Inference for Extracting Soft Biometric
Text Descriptorsfrom Patient Triage Images

Niyati Chhaya

10:00am Friday, 24 August 2012, ITE 325b, UMBC

Disaster events can result in mass casualties and missing persons, giving rise to a need to provide information about victims to the public. This can be achieved by digitally documenting information available at emergency medical care centers in the form of pictures. The images and other identifying information, such as fingerprints, cannot be broadcast due to privacy concerns, leading to a need to extract appearance-related non-unique features from this data to facilitate locating missing persons. Using humans and machines to compare images is not feasible due to the scale of the situation and the nature (presence of blood and debris) of the images. Extracting a soft biometric text descriptor (text labels describing different soft biometric features) makes it possible to organize information about individuals from these images in a searchable format without revealing the person's identity. The main aim of this thesis is to extract soft biometric features from person images to label appearance-related information and make it available as a text descriptor.

We begin by presenting soft biometric feature detectors for patient images that include an ensemble-based face detection algorithm, template-based eye detection, and eyeglasses, hair color, and skin color detection. We also present a facial hair detector that uses a combination of face and hair information. The feature detection results indicate a need to combine and exploit feature relationships for better performance. We propose a novel probabilistic graphical model that consists of different feature detectors and exploits relationships between these features using a message-passing inference algorithm to build a coherent text descriptor. Further, to understand the utility and the nature of the text descriptors, we present a study based on human descriptions that aims at extracting order and structure information about the features.

We evaluate the performance of individual feature detectors for standard and triage images and establish the challenges posed by the latter. Further, our text analysis shows extreme variability in human descriptions. However, we succeed in extracting some insights about the order of a natural text description. Through our evaluations of the graphical model, we show that for different feature detectors, datasets, and graph sizes the graphical model helps improve the accuracy of the text output. We also show that the performance of the graphical model depends on the individual nodes (feature detectors) and that the model can be used to improve the performance of the individual feature detectors. This thesis illustrates the whole process from images to text descriptors while evaluating components as we proceed. This work presents an approach to extract text labels from images using computer vision, a probabilistic graphical model, and natural language processing techniques.

Committee: Drs. Dr. Tim Oates (Chair), Marie desJardins, Tim Finin, Glenn Pearson and Jesus Caban

CSEE Professor Dr. Alan Sherman (PI) and Dr. Rick Forno (Co-PI), Graduate Program Director, Cybersecurity have received an NSF grant of $2.5 million over five years to fund 22 students studying Information Assurance (IA) and Cybersecurity. The scholarships are part of the Federal Cyber Scholarship for Service (SFS) program.

Future scholars will come from UMBC’s undergraduate, graduate, and professional studies programs. In addition to a generous full-ride scholarship, scholars are granted an annual stipend during their last two or three years.  The yearly stipends are $20,000 for underdergraduate, $25,000 for M.S. and $30,000 for PhD students.  Students will also engage in paid summer internships with federal government agencies and have opportunities to carry out mentored research projects at UMBC and its cyber partners from government and industry.

“Our goal is to encourage students to pursue cybersecurity education at UMBC and then move into careers that can build upon their education,” explains Dr. Forno. “The SFS program is one way to do that, with the outcome being to provide educated, qualified and highly competent cybersecurity practitioners to the federal government.”

The scholarships will be coordinated through UMBC’s Center for Information Security and Assurance (CISA), and both CISA and UMBC’s Cyber Defense Lab (CDL) will play a key role in the overall academic experience of the SFS scholars.

Along with the monetary award come a few scholarship program requirements. During their scholarship period (typically two years), students are required to intern at a federal organization. After graduation, scholars must serve at a Federal agency in an information assurance position for one to two years, depending on their level of support.

During the upcoming 2012-2013 school year, the program will support two Masters students and two Master in Professional Studies students, though in the future, one B.S., two M.S., two M.P.S., and one Ph.D. students will be supported annually.

Degree-seeking students in Computer Science, Computer Engineering, or any related field, including Electrical Engineering, Math, Physics, Information Systems, Public Policy, or Education, are eligible. “We are interested in fostering a diverse group of SFS scholars,” says Forno. “To that end, we intend to work closely with groups like CWIT and the Meyerhoff Scholars (among others) to help in our outreach and recruiting efforts in this critical academic discipline.” To learn more about applying for the scholarship, visit the CISA scholarship oppotunities page.

The grant will also fund a new one-day annual regional workshop that will focus on innovations for K-12, undergraduate, and graduate cybersecurity education. The goal is to develop "innovative, relevant, meaningful, and real-world oriented pedagogical materials that can be applied across the academic spectrum in conducting cybersecurity education."

The scholarship program, coupled with UMBC’s location at the “epicenter of cybersecurity,” will further mark UMBC as a pioneer in the field. “We all know that cybersecurity is a hot field and of critical national interest," says Forno. "UMBC’s strength in Computer Science, Cybersecurity, and related STEM fields, combined with our reputation for producing qualified technologitsts makes our participation in SFS very attractive both to the school and our current and future students.”

Tim Finin and Anupam Joshi have received a $400,000 research award from the NSF Secure and Trustworthy Cyberspace (SaTC) program for a three year project to investigate how to better manage security and privacy constraints while querying semantically annotated linked data sources. The project, Policy Compliant Integration of Linked Data, is a collaboration with researchers at M.I.T. and the University of Texas at Dallas.

The ubiquity of computing technology and the Internet have created an age of big data that has the potential to greatly enhance the efficiency of our societies and the well-being of all people. The trend comes with problems that threaten to prevent or undermine the benefits. An immediate concern is how to fuse, integrate and analyze data while respecting privacy, security and usage concerns. A second issue is allowing data to remain distributed, enabling its owners to maintain and control quality as well as to enforce security and privacy policies. A final underlying challenge is helping to produce sound and useful results by assuring that systems understand the meaning of the data being integrated and analyzing access and usage policies. For some domains, like health informatics and clinical research, solving these problems will have a significant impact on society.

This project explores an approach to solving these problems by developing a policy-compliant integration system for linked healthcare data. The system models data, schemas and policies using open Web standards such as Semantic Web languages, federates queries to independent Linked Data stores based on content, provides policy enforcement by modifying incompliant queries, and uses formal methods to guarantee correctness of key components.

This project provides new approaches to solving one of the most significant problems our society faces in the 21st century: benefiting from the integration of distributed linked data while respecting security, privacy, and usage requirements. The prototype tools and systems are incorporated into our educational activities and made available to others via appropriate open source licenses.