3 research outputs found
Finding Your Literature Match -- A Recommender System
The universe of potentially interesting, searchable literature is expanding
continuously. Besides the normal expansion, there is an additional influx of
literature because of interdisciplinary boundaries becoming more and more
diffuse. Hence, the need for accurate, efficient and intelligent search tools
is bigger than ever. Even with a sophisticated search engine, looking for
information can still result in overwhelming results. An overload of
information has the intrinsic danger of scaring visitors away, and any
organization, for-profit or not-for-profit, in the business of providing
scholarly information wants to capture and keep the attention of its target
audience. Publishers and search engine engineers alike will benefit from a
service that is able to provide visitors with recommendations that closely meet
their interests. Providing visitors with special deals, new options and
highlights may be interesting to a certain degree, but what makes more sense
(especially from a commercial point of view) than to let visitors do most of
the work by the mere action of making choices? Hiring psychics is not an
option, so a technological solution is needed to recommend items that a visitor
is likely to be looking for. In this presentation we will introduce such a
solution and argue that it is practically feasible to incorporate this approach
into a useful addition to any information retrieval system with enough usage.Comment: Contribution to the proceedings of the colloquium Future Professional
Communication in Astronomy II, 13-14 April 2010, Cambridge, Massachusetts. 11
pages, 4 figures
The Emerging Scholarly Brain
It is now a commonplace observation that human society is becoming a coherent
super-organism, and that the information infrastructure forms its emerging
brain. Perhaps, as the underlying technologies are likely to become billions of
times more powerful than those we have today, we could say that we are now
building the lizard brain for the future organism.Comment: to appear in Future Professional Communication in Astronomy-II
(FPCA-II) editors A. Heck and A. Accomazz
Finding and Recommending Scholarly Articles
The rate at which scholarly literature is being produced has been increasing
at approximately 3.5 percent per year for decades. This means that during a
typical 40 year career the amount of new literature produced each year
increases by a factor of four. The methods scholars use to discover relevant
literature must change. Just like everybody else involved in information
discovery, scholars are confronted with information overload. Two decades ago,
this discovery process essentially consisted of paging through abstract books,
talking to colleagues and librarians, and browsing journals. A time-consuming
process, which could even be longer if material had to be shipped from
elsewhere. Now much of this discovery process is mediated by online scholarly
information systems. All these systems are relatively new, and all are still
changing. They all share a common goal: to provide their users with access to
the literature relevant to their specific needs. To achieve this each system
responds to actions by the user by displaying articles which the system judges
relevant to the user's current needs. Recently search systems which use
particularly sophisticated methodologies to recommend a few specific papers to
the user have been called "recommender systems". These methods are in line with
the current use of the term "recommender system" in computer science. We do not
adopt this definition, rather we view systems like these as components in a
larger whole, which is presented by the scholarly information systems
themselves. In what follows we view the recommender system as an aspect of the
entire information system; one which combines the massive memory capacities of
the machine with the cognitive abilities of the human user to achieve a
human-machine synergy.Comment: 14 pages, part of the forthcoming MIT book "Bibliometrics and Beyond:
Metrics-Based Evaluation of Scholarly Research" edited by Blaise Cronin and
Cassidy R. Sugimot