Computing semantic relatedness from human navigational paths on Wikipedia
P. Singer, T. Niebler, M. Strohmaier, and A. Hotho. Proceedings of the 22nd international conference on World Wide Web companion, page 171--172. Republic and Canton of Geneva, Switzerland, International World Wide Web Conferences Steering Committee, (2013)
Abstract
This paper presents a novel approach for computing semantic relatedness between concepts on Wikipedia by using human navigational paths for this task. Our results suggest that human navigational paths provide a viable source for calculating semantic relatedness between concepts on Wikipedia. We also show that we can improve accuracy by intelligent selection of path corpora based on path characteristics indicating that not all paths are equally useful. Our work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.
Description
Computing semantic relatedness from human navigational paths on Wikipedia
%0 Conference Paper
%1 singer2013computing
%A Singer, Philipp
%A Niebler, Thomas
%A Strohmaier, Markus
%A Hotho, Andreas
%B Proceedings of the 22nd international conference on World Wide Web companion
%C Republic and Canton of Geneva, Switzerland
%D 2013
%E ACM,
%I International World Wide Web Conferences Steering Committee
%K app_nlp from:thoni human myown navigational paths posts postsi relatedness research_representation_learning selected semantic wikipedia
%P 171--172
%T Computing semantic relatedness from human navigational paths on Wikipedia
%U http://dl.acm.org/citation.cfm?id=2487788.2487873
%X This paper presents a novel approach for computing semantic relatedness between concepts on Wikipedia by using human navigational paths for this task. Our results suggest that human navigational paths provide a viable source for calculating semantic relatedness between concepts on Wikipedia. We also show that we can improve accuracy by intelligent selection of path corpora based on path characteristics indicating that not all paths are equally useful. Our work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.
%@ 978-1-4503-2038-2
@inproceedings{singer2013computing,
abstract = {This paper presents a novel approach for computing semantic relatedness between concepts on Wikipedia by using human navigational paths for this task. Our results suggest that human navigational paths provide a viable source for calculating semantic relatedness between concepts on Wikipedia. We also show that we can improve accuracy by intelligent selection of path corpora based on path characteristics indicating that not all paths are equally useful. Our work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.},
acmid = {2487873},
added-at = {2016-10-11T20:49:01.000+0200},
address = {Republic and Canton of Geneva, Switzerland},
author = {Singer, Philipp and Niebler, Thomas and Strohmaier, Markus and Hotho, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/2356cbc2b1ad50897cc88ff6eb6ccb351/dmir},
booktitle = {Proceedings of the 22nd international conference on World Wide Web companion},
description = {Computing semantic relatedness from human navigational paths on Wikipedia},
editor = {ACM},
interhash = {c8651bff5f9f8130c8660f979941df42},
intrahash = {356cbc2b1ad50897cc88ff6eb6ccb351},
isbn = {978-1-4503-2038-2},
keywords = {app_nlp from:thoni human myown navigational paths posts postsi relatedness research_representation_learning selected semantic wikipedia},
location = {Rio de Janeiro, Brazil},
numpages = {2},
pages = {171--172},
publisher = {International World Wide Web Conferences Steering Committee},
series = {WWW '13 Companion},
timestamp = {2024-05-16T13:39:43.000+0200},
title = {Computing semantic relatedness from human navigational paths on Wikipedia},
url = {http://dl.acm.org/citation.cfm?id=2487788.2487873},
year = 2013
}