Temporal web dynamics and its application to information retrieval

Abstract

The World Wide Web is highly dynamic and is constantly evolving to cover the latest information about the physical and social updates in the world. At the same time, the changes in web contents are entangled with new information needs and time-sensitive user interactions with information sources. To address these temporal information needs effectively, it is essential for the search engines to model web dynamics and understand the changes in user behavior over time that are caused by them.In this full-day tutorial, we focus on modeling time-sensitive content on the web, and discuss the state-of-the-art approaches for integrating temporal signals in web search. We address many of the related research topics including those associated with searching dynamic collections, defining timesensitive relevance, understanding user query behavior over time, and investigating the main reasons behind content changes. We also cover algorithms, evaluation methodologies and metrics for time-aware search, and discuss the latest breakthroughs and open challenges.

Studying Ranking-Incentivized Web Dynamics

“…There is work on predicting and analyzing changes of Web pages; e.g., [13,14]. These studies are for general dynamics and not for ranking-oriented dynamics which we address in this paper.…”

Approches de classification pour le filtrage de documents importants au sujet d’une entité nommée

“…De nombreux facteurs comme la périodicité des centres d'intérêts des utilisateurs (Yom-Tov, Diaz, 2011), la répétition d'une même information dans de nombreux documents, la complémentarité de différentes sources d'information comme les sites de nouvelles journalistiques et les blogs (König et al, 2009), les réseaux sociaux (Dong et al, 2010) ou encore la nouveauté rentrent en jeu (Del Corso et al, 2005). (Radinsky et al, 2013) présentent une vaste vue d'ensemble des résultats et applications de l'analyse et de la prise en compte de la composante temporelle pour la recherche d'information.…”

Driving the Herd: Search Engines as Content Influencers

“…Despite their far reaching -societal and other -implications, the effects of rankings induced by search engines on content in the corpus have attracted very little research attention [3,23]. Indeed, the large body of prior work on studying content changes in the Web was performed regardless of ranking effects (e.g., [20,21,25]).…”