Select, Link and Rank: Diversified Query Expansion and Entity Ranking using Wikipedia

A search query, being a very concise grounding of user intent, could potentially have many possible interpretations. Search engines hedge their bets by diversifying top results to cover multiple such possibilities so that the user is likely to be satisfied, whatever be her intended interpretation. Diversified Query Expansion is the problem of diversifying query expansion suggestions, so that the user can specialize the query to better suit her intent, even before perusing search results. We propose a method, Select-Link-Rank, that exploits semantic information from Wikipedia to generate diversified query expansions. SLR does collective processing of terms and Wikipedia entities in an integrated framework, simultaneously diversifying query expansions and entity recommendations. SLR starts with selecting informative terms from search results of the initial query, links them to Wikipedia entities, performs a diversity-conscious entity scoring and transfers such scoring to the term space to arrive at query expansion suggestions. Through an extensive empirical analysis and user study, we show that our method outperforms the state-of-the-art diversified query expansion and diversified entity recommendation techniques.

On the road from consultation cynicism to energising e-consultation

A major concern in recent political discourse is that government has become both isolated from and unresponsive to its citizens. Democracy, by definition, demands a two-way flow of communication between government and civil society and it is now commonly argued that ICTs have the potential to facilitate such improved flows of communication--hence, e-democracy and e-consultation. The preliminary research findings presented here are part of a larger ongoing research project on e-consultation on the island of Ireland (see http://e-consultation.org). The paper initially draws on focus group discussions on the theme of (e)consultation conducted amongst activist citizens. High levels of frustration, scepticism and cynicism were expressed on the form, nature and process of extant consultation processes. The main focus addressed in this paper, however, is on how these citizens envisage ICT being used in future e-consultations. In general, most focus group participants were open to the use of ICT in future e-consultation processes but the consensus was that community groups did not currently have access to an appropriate level or range of infrastructure, technologies or skills. As a follow up to the focus group findings the research group ran a number of demonstrations on e-consultation technologies with invited activist citizens. Technologies introduced included chat room, video-conferencing, WikiPedia, WebIQ, Zing and others. The main preliminary findings and feedback from one such demonstration, and our own observations, are then presented which suggest that the potential does exist for using e-consultation technologies in local democracy and in local government to drive positive change in the government-citizen relationship. We present no na�¯ve solutions here; we merely point to some possibilities and we acknowledge that ICT alone is very unlikely to be a panacea for the declining levels of citizen participation in most democratic societies.

Arching or Compressive Membrane Action in Reinforced Concrete Slabs

Arching or compressive membrane action (CMA) in reinforced concrete slabs occurs as a result of the great difference between the tensile and compressive strength of concrete. Cracking of the concrete causes a migration of the neutral axis which is accompanied by in-plane expansion of the slab at its boundaries. If this natural tendency to expand is restrained, the development of arching action enhances the strength of the slab. The term arching action is normally used to describe the arching phenomenon in one-way spanning slabs and compressive membrane action is normally used to describe the arching phenomenon in two-
way spanning slabs. This encyclopedic article presents the background to the discovery of the phenomenon of arching action and presents a factual history of the approaches to the treatment of arching action in the United Kingdom and North American bridge deck design codes. The article summarises the theoretical methodology used in the United Kingdom Design Manual for Roads and Bridges, BD81/02, which was based on the work by Kirkpatrick, Rankin & Long at Queen's University Belfast.

Entity Linking for Web Search Queries

We consider the problem of linking web search queries to entities from a knowledge base such as Wikipedia. Such linking enables converting a user’s web search session to a footprint in the knowledge base that could be used to enrich the user profile. Traditional methods for entity linking have been directed towards finding entity mentions in text documents such as news reports, each of which are possibly linked to multiple entities enabling the usage of measures like entity set coherence. Since web search queries are very small text fragments, such criteria that rely on existence of a multitude of mentions do not work too well on them. We propose a three-phase method for linking web search queries to wikipedia entities. The first phase does IR-style scoring of entities against the search query to narrow down to a subset of entities that are expanded using hyperlink information in the second phase to a larger set. Lastly, we use a graph traversal approach to identify the top entities to link the query to. Through an empirical evaluation on real-world web search queries, we illustrate that our methods significantly enhance the linking accuracy over state-of-the-art methods.

Learning from Outdoor Webcams: Surveillance of Physical Activity Across Environments

Abstract
Publicly available, outdoor webcams continuously view the world and share images. These cameras include traffic cams, campus cams, ski-resort cams, etc. The Archive of Many Outdoor Scenes (AMOS) is a project aiming to geolocate, annotate, archive, and visualize these cameras and images to serve as a resource for a wide variety of scientific applications. The AMOS dataset has archived over 750 million images of outdoor environments from 27,000 webcams since 2006. Our goal is to utilize the AMOS image dataset and crowdsourcing to develop reliable and valid tools to improve physical activity assessment via online, outdoor webcam capture of global physical activity patterns and urban built environment characteristics.
This project’s grand scale-up of capturing physical activity patterns and built environments is a methodological step forward in advancing a real-time, non-labor intensive assessment using webcams, crowdsourcing, and eventually machine learning. The combined use of webcams capturing outdoor scenes every 30 min and crowdsources providing the labor of annotating the scenes allows for accelerated public health surveillance related to physical activity across numerous built environments. The ultimate goal of this public health and computer vision collaboration is to develop machine learning algorithms that will automatically identify and calculate physical activity patterns.