5 citations · 11 across the 6 of their papers we have counts for
6 papers
On the Estimation and Use of Statistical Modelling in Information Retrieval
Casper Petersen
Several tasks in information retrieval (IR) rely on assumptions regarding the distribution of some property (such as term frequency) in the data being processed. This thesis argues…
Adaptive Distributional Extensions to DFR Ranking
Casper Petersen, Jakob Grue Simonsen, Kalervo Jarvelin +1
Divergence From Randomness (DFR) ranking models assume that informative terms are distributed in a corpus differently than non-informative terms. Different statistical models (e.g.…
Exploiting the Bipartite Structure of Entity Grids for Document Coherence and Retrieval
Christina Lioma, Fabien Tarissan, Jakob Grue Simonsen +2
Document coherence describes how much sense text makes in terms of its logical organisation and discourse flow. Even though coherence is a relatively difficult notion to quantify p…
Deep Learning Relevance: Creating Relevant Information (as Opposed to Retrieving it)
Christina Lioma, Birger Larsen, Casper Petersen +1
What if Information Retrieval (IR) systems did not just retrieve relevant information that is stored in their indices, but could also "understand" it and synthesise it into a singl…
Entropy and Graph Based Modelling of Document Coherence using Discourse Entities: An Application
Casper Petersen, Christina Lioma, Jakob Grue Simonsen +1
We present two novel models of document coherence and their application to information retrieval (IR). Both models approximate document coherence using discourse entities, e.g. the…
Near-optimal adjacency labeling scheme for power-law graphs
Casper Petersen, Noy Rotbart, Jakob Grue Simonsen +1
An adjacency labeling scheme is a method that assigns labels to the vertices of a graph such that adjacency between vertices can be inferred directly from the assigned label, witho…