News

School Seminars: Building the News Search Engine – Bloomberg

Building the news search engine, by Ramkumar Aiyengar, Bloomberg
Abstract:
This talk provides an insight into the challenges involved in providing near real-time news search to Bloomberg customers. Our News team is in the process of migrating to using Solr/Lucene as its search and alerting backend. This talk starts with a picture of what’s involved in building such a backend, then delves into what makes up a search engine, and then discusses the challenges of scaling up for low-latency and high-load.
Bio:
Ramkumar leads the News Search backend team at the Bloomberg R&D office in London. He joined Bloomberg from his university in India and has been with the News R&D team for 7 years now. For the last couple of years, his team has focussed on rewriting almost the entire search/alert backend, used by almost every Bloomberg user to get near-real time access to news with sub-second latencies. A geek at heart, he considers himself a Linux evangelist, an open source enthusiast, and one of those weird creatures who believes that Emacs is an operating system and had once got his music player and playlists to be controlled through a library written in Lisp.

Event details

  • When: 3rd March 2015 14:00 - 15:00
  • Where: Cole 1.33
  • Series: CS Colloquia Series, School Seminar Series
  • Format: Seminar, Talk

Administrative Data Research Centre – Scotland, St Andrews team

The Scottish ADRC is led by Chris Dibben at the University of Edinburgh, and is supported by the Economic and Social Research Council. The ADRC – Scotland:

  • Brings together major Scottish centres of research, and builds on predecessor organisation structures, involving secondary analysis of public-sector data in order to create a common framework for research based on an integrated data linkage service These groups, funded by research councils, charities and Government, include the Scottish Longitudinal Study (SLS), Administrative Data Liaison Service (ADLS), the UK Census and Administrative data LongitudinaL hub (CALLS), Applied Quantitative Methods Network (AQMeN), Scottish Health Informatics Centre (SHIP) and eHealth Research Centre (eHIRC), the national digital data centre (EDINA), Centre for Research on Environment Society and Health (CRESH) and the Centre for Cognitive Ageing & Cognitive Epidemiology.
  • Involves world leading experts in the theory, methods and policy of record linkage for secondary uses, including public engagement, ethics, information governance and law; linkage and analysis of large datasets; geocoding, natural language processing and machine learning. This includes experts from a range of sectors from which administrative data is derived including housing, transport, income, labour markets, health, crime and criminal justice, education, social services.
  • Builds on existing services – enabling immediate access to state-of-the-art facilities for research access to de-identified administrative data by accredited researchers.
  • Co-locates with the Scotland hub of national health informatics research endeavour, which has already brought together key infrastructures, technologists and research groups, enabling synergies and collaborations that will ensure rapid progress towards a national informatics centre of world importance.
  • Exploits Scotland’s unique holding of linked, machine readable, historical administrative data, including the 1932 and 1947 Scottish Mental Surveys, civil registration data (1855-present), Aberdeen Children of the Nineteen Fifties (ACONF), and others, to make available powerful administrative data based cohort and longitudinal studies.
  • Aims to support National Records of Scotland (NRS) in their work exploring alternatives to the traditional decennial based census.
  • Will have a significant programme of public engagement – including working with citizens to produce statistics of use and relevance to them, and press engagement to ensure that accurate messages are reported.
  • The ADRC research programme will inform the entire UK Administrative Data Research Network and produce research – both specific to administrative data use and more broadly social science – world-leading in terms of originality, significance and rigour.

The St Andrews team will lead research in data linkage methodology, and are currently investigating the potential to use prefabricated secure rooms within the premises of institutions where researchers require secure access to sensitive data.

The St Andrews team involves:

  • Graham Kirby, Alan Dearle – researchers
  • Darren Lightfoot – project manager
  • 2-year research fellow to be appointed summer 2015

The data linkage methodology research programme also includes Alasdair Gray at Heriot-Watt and Peter Christen at Australian National University.

CoDiMa (CCP in the area of Computational Discrete Mathematics)

Steve Linton and Alexander Konovalov were successful in the application for the EPSRC-funded Collaborative Computational Project called CoDiMa (CCP in the area of Computational Discrete Mathematics): CoDiMa (CCP in the area of Computational Discrete Mathematics)

CoDiMa is centred on two open source software systems: GAP and SAGE which are already widely used for research and teaching in abstract algebra, number theory, cryptography, combinatorics, graph theory, coding theory, optimisation and search, among other areas.

The CCP aims to support the ecosystem of users, extenders and developers of these systems and encourage best practice in their use, and to support the more rapid uptake of new features such as parallel programming support.

The project will run for 5 years starting from March 1st, 2015.

A PhD studentship, in collaboration with MSR (Cambridge)

Reasoning about Racy Programs under Relaxed Consistency

A PhD studentship, in collaboration with MSR (Cambridge)

http://research.microsoft.com/en-us/collaboration/global/apply-europe.aspx>

Each Microsoft scholarship consists of an annual bursary up to a maximum of three years. The amount varies in different countries and may depend on specific arrangement with public research funding agencies. The bursary continues automatically the following years, provided the Scholar meets the requirements of the institution.

Payment is made to the institution. The amount of the scholarship is the maximum amount Microsoft Research pays to the institution. In addition, every Scholar receives a laptop allowance.

During the course of their PhD, Scholars are invited to Microsoft Research in Cambridge for a PhD Summer School that includes a series of talks of academic interest and posters sessions, which provides the Scholars the opportunity to present their work to Microsoft researchers and a number of Cambridge academics.

Some of the Scholars may also be offered—at the sole discretion of Microsoft Research—an internship in one of the Microsoft Research laboratories. Internships involve working on a project alongside and as part of a team of Microsoft researchers. Scholars are paid during their internship—in addition to their scholarship bursary. Interested Scholars can apply through the Microsoft Research internship website.

 

Notable Woman in Computing Card Deck

Available on a coffee table (Jack Cole) near you: Notable Women in Computing playing card deck featuring 54 notable women in computer science. Play your favourite card game and learn more about the history and future of women in computer science. Read more about the KickStarter and Wiki Project.

WIC

Ae fond farewell: Anne and Joy

As we start a new semester, we take time to reflect on those leaving the department. Fare thee well Anne and Joy. The School hosted a retirement reception for them last week. We thank them for all their hard work over many years and their contribution to making the School such a great place to work and study. They are pictured below being presented with flowers and keepsakes.

reception

School Seminar Series: Matching in Practice: Junior Doctor Allocation and Kidney Exchange

Matching in Practice: Junior Doctor Allocation and Kidney Exchange by Dr. David Manlove

Abstract:
Matching problems typically involve assigning agents to commodities, possibly on the basis of ordinal preferences or other metrics. These problems have large-scale applications to centralised matching schemes in many countries and contexts. In this talk I will describe the matching problems featuring in two such schemes in the UK that have involved collaborations between the National Health Service and the University of Glasgow. One of these dealt with the allocation of junior doctors to Scottish hospitals (1999-2012), and the other is concerned with finding kidney exchanges among incompatible donor-patient pairs across the UK (2007-date). In each case I will describe the applications, present the underlying algorithmic problems, outline the computational methods for their solution and give an overview of results arising from real data connected with the matching schemes in recent years.

BIO:
David Manlove is a Senior Lecturer at the School of Computing Science, University of Glasgow, where he has been since 1995. His research interests lie mainly in the field of algorithms and complexity, and include algorithms for matching problems involving preferences. These arise in applications such as the assignment of school leavers to universities, kidney patients to donors and junior doctors to hospitals. He and his colleagues have been involved in collaborations with the NHS in relation to the Scottish Foundation Allocation Scheme (for matching junior doctors to hospitals) and the National Living Donor Kidney Sharing Schemes (for enabling kidney “swaps” between incompatible donor-patient pairs) where optimal matching algorithms developed by him and colleagues have been deployed. He has over 50 publications in this area including his book “Algorithmics of Matching Under Preferences”, published in 2013.

Event details

  • When: 3rd February 2015 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Talk

School Seminar Series: Statistically Consistent Estimation and Efficient Inference for Natural Language Parsing

Statistically Consistent Estimation and Efficient Inference for
Natural Language ParsingBy Shay Cohen, University of Edinburgh.

Abstract:
In the past few years, there has been an increased interest in the machinel earning community in spectral algorithms for estimating models with latent variables. Examples include algorithms for estimating mixture of Gaussians or for estimating the parameters of a hidden Markov model.

The EM algorithm has been the mainstay for estimation with latent variables, but because it is guaranteed to converge to a local maximum of the likelihood, it is not a consistent estimator. Spectral algorithms, on the other hand, are often shown to be consistent. They are often more computationally efficient than EM.

In this talk, I am interested in presenting two types for spectral algorithms for latent-variable PCFGs, a model widely used in the NLP community for parsing. One algorithm is for consistent estimation of L-PCFGs, and the other is for efficient inference with L-PCFGs (or PCFGs). Both algorithms are based on linear-algebraic formulation of L-PCFGs and PCFGs.

BIO:
Shay Cohen is a Chancellor’s fellow (assistant professor) at the University of Edinburgh (School of Informatics). Before that, he was a postdoctoral research scientist in the Department of Computer Science at Columbia University, and held an NSF/CRA Computing Innovation Fellowship. He received his B.Sc. and M.Sc. from Tel Aviv University in 2000 and 2004, and his Ph.D. from Carnegie Mellon University in 2011. His research interests span a range of topics in natural language processing and machine learning, with a focus on structured prediction. He is especially interested in developing efficient and scalable parsing algorithms as well as learning algorithms for probabilistic grammars.

Event details

  • When: 21st January 2015 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Talk

Research Evaluation Framework 2014

The results of the UK Research Evaluation Framework 2014 were released publicly today. The School of Computer Science was rated 14th in the UK (and a close 2nd in Scotland) in terms of research outputs, which is a measure of how our research compares to the best in the world. Over 30% of our submitted papers received the highest 4* ranking, with a further 55% receiving the 3* ranking.

“We’re delighted with this result,” said Prof Steve Linton, the Head of School. “Coming alongside our top placement in the UK for teaching Computer Science, it shows that that we’ve managed to achieve a balance between our two core activities while maintaining the quality of each.  It’s a confirmation of our high standing in the subject and leaves us excited for future developments.”

On the broader evaluation metrics that include research environment and non-academic impact, as well as research quality, the School was ranked 27th in the UK (4th in Scotland). “We submitted three impact case studies ranging from cloud computing to improving cultural engagement through virtual reality,” said Prof Simon Dobson, the School’s Director of Research. “These are all strategic areas that we’ll be keen to build on.”

Institutionally, the University of St Andrews was ranked 19th overall in the UK, and 2nd in Scotland.