30,843 research outputs found
Reply With: Proactive Recommendation of Email Attachments
Email responses often contain items-such as a file or a hyperlink to an
external document-that are attached to or included inline in the body of the
message. Analysis of an enterprise email corpus reveals that 35% of the time
when users include these items as part of their response, the attachable item
is already present in their inbox or sent folder. A modern email client can
proactively retrieve relevant attachable items from the user's past emails
based on the context of the current conversation, and recommend them for
inclusion, to reduce the time and effort involved in composing the response. In
this paper, we propose a weakly supervised learning framework for recommending
attachable items to the user. As email search systems are commonly available,
we constrain the recommendation task to formulating effective search queries
from the context of the conversations. The query is submitted to an existing IR
system to retrieve relevant items for attachment. We also present a novel
strategy for generating labels from an email corpus---without the need for
manual annotations---that can be used to train and evaluate the query
formulation model. In addition, we describe a deep convolutional neural network
that demonstrates satisfactory performance on this query formulation task when
evaluated on the publicly available Avocado dataset and a proprietary dataset
of internal emails obtained through an employee participation program.Comment: CIKM2017. Proceedings of the 26th ACM International Conference on
Information and Knowledge Management. 201
Report on the Second International Workshop on the Evaluation on Collaborative Information Seeking and Retrieval (ECol'2017 @ CHIIR)
The 2nd workshop on the evaluation of collaborative information retrieval and seeking (ECol) was held in conjunction with the ACM SIGIR Conference on Human Information Interaction & Retrieval (CHIIR) in Oslo, Norway. The workshop focused on discussing the challenges and difficulties of researching and studying collaborative information retrieval and seeking (CIS/CIR). After an introductory and scene setting overview of developments in CIR/CIS, participants were challenged with devising a range of possible CIR/CIS tasks that could be used for evaluation purposes. Through the brainstorming and discussions, valuable insights regarding the evaluation of CIR/CIS tasks become apparent ? for particular tasks efficiency and/or effectiveness is most important, however for the majority of tasks the success and quality of outcomes along with knowledge sharing and sense-making were most important ? of which these latter attributes are much more difficult to measure and evaluate. Thus the major challenge for CIR/CIS research is to develop methods, measures and methodologies to evaluate these high order attributes
Online behaviour of luxury brand advocates: differences between active advocates and passive loyalists
The study aims to identify online behaviours of luxury brand advocates referring to differentiation between active and passive loyalists. A netnographic approach was used to observe groups of luxury handbag advocates. Key findings include an identification of engagement manifested in positive word of mouth and enthusiastic brand recommendation. Advocates routinely share their love of particular brands, openly expressing joy and sharing heightened levels of self-esteem. Engaged passive loyalists tend to share less with peers, but instead celebrate their purchases more personally
Planets: Integrated Services for Digital Preservation
The Planets Project is developing services and technology to address core challenges in digital preservation. This article introduces the motivation for this work, describes the extensible technical architecture and places the Planets approach into the context of the Open Archival Information System (OAIS) Reference Model. It also provides a scenario demonstrating Planetsâ usefulness in solving real-life digital preservation problems and an overview of the projectâs progress to date
Automatic Metadata Generation using Associative Networks
In spite of its tremendous value, metadata is generally sparse and
incomplete, thereby hampering the effectiveness of digital information
services. Many of the existing mechanisms for the automated creation of
metadata rely primarily on content analysis which can be costly and
inefficient. The automatic metadata generation system proposed in this article
leverages resource relationships generated from existing metadata as a medium
for propagation from metadata-rich to metadata-poor resources. Because of its
independence from content analysis, it can be applied to a wide variety of
resource media types and is shown to be computationally inexpensive. The
proposed method operates through two distinct phases. Occurrence and
co-occurrence algorithms first generate an associative network of repository
resources leveraging existing repository metadata. Second, using the
associative network as a substrate, metadata associated with metadata-rich
resources is propagated to metadata-poor resources by means of a discrete-form
spreading activation algorithm. This article discusses the general framework
for building associative networks, an algorithm for disseminating metadata
through such networks, and the results of an experiment and validation of the
proposed method using a standard bibliographic dataset
Real-Time Recommendation of Streamed Data
This tutorial addressed two trending topics in the field of recommender systems research, namely A/B testing and real-time recommendations of streamed data. Focusing on the news domain, participants learned how to benchmark the performance of stream-based recommendation algorithms in a live recommender system and in a simulated environment
Recommendation, collaboration and social search
This chapter considers the social component of interactive information retrieval: what is the role of other people in searching and browsing? For simplicity we begin by considering situations without computers. After all, you can interactively retrieve information without a computer; you just have to interact with someone or something else. Such an analysis can then help us think about the new forms of collaborative interactions that extend our conceptions of information search, made possible by the growth of networked ubiquitous computing technology.
Information searching and browsing have often been conceptualized as a solitary activity, however they always have a social component. We may talk about 'the' searcher or 'the' user of a database or information resource. Our focus may be on individual uses and our research may look at individual users. Our experiments may be designed to observe the behaviors of individual subjects. Our models and theories derived from our empirical analyses may focus substantially or exclusively on an individual's evolving goals, thoughts, beliefs, emotions and actions. Nevertheless there are always social aspects of information seeking and use present, both implicitly and explicitly.
We start by summarizing some of the history of information access with an emphasis on social and collaborative interactions. Then we look at the nature of recommendations, social search and interfaces to support collaboration between information seekers. Following this we consider how the design of interactive information systems is influenced by their social elements
Bots, Seeds and People: Web Archives as Infrastructure
The field of web archiving provides a unique mix of human and automated
agents collaborating to achieve the preservation of the web. Centuries old
theories of archival appraisal are being transplanted into the sociotechnical
environment of the World Wide Web with varying degrees of success. The work of
the archivist and bots in contact with the material of the web present a
distinctive and understudied CSCW shaped problem. To investigate this space we
conducted semi-structured interviews with archivists and technologists who were
directly involved in the selection of content from the web for archives. These
semi-structured interviews identified thematic areas that inform the appraisal
process in web archives, some of which are encoded in heuristics and
algorithms. Making the infrastructure of web archives legible to the archivist,
the automated agents and the future researcher is presented as a challenge to
the CSCW and archival community
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