Peer assessment in MOOCs: Systematic literature review
We report on a systematic review of the landscape of peer assessment in massive open
online courses (MOOCs) with papers from 2014 to 2020 in 20 leading education technology …
online courses (MOOCs) with papers from 2014 to 2020 in 20 leading education technology …
Search result diversification
Ranking in information retrieval has been traditionally approached as a pursuit of relevant
information, under the assumption that the users' information needs are unambiguously …
information, under the assumption that the users' information needs are unambiguously …
Big & personal: data and models behind netflix recommendations
X Amatriain - Proceedings of the 2nd international workshop on big …, 2013 - dl.acm.org
Since the Netflix $1 million Prize, announced in 2006, our company has been known to have
personalization at the core of our product. Even at that point in time, the dataset that we …
personalization at the core of our product. Even at that point in time, the dataset that we …
Learning for search result diversification
Search result diversification has gained attention as a way to tackle the ambiguous or multi-
faceted information needs of users. Most existing methods on this problem utilize a heuristic …
faceted information needs of users. Most existing methods on this problem utilize a heuristic …
Coactive learning
P Shivaswamy, T Joachims - Journal of Artificial Intelligence Research, 2015 - jair.org
We propose Coactive Learning as a model of interaction between a learning system and a
human user, where both have the common goal of providing results of maximum utility to the …
human user, where both have the common goal of providing results of maximum utility to the …
Learning maximal marginal relevance model via directly optimizing diversity evaluation measures
In this paper we address the issue of learning a ranking model for search result
diversification. In the task, a model concerns with both query-document relevance and …
diversification. In the task, a model concerns with both query-document relevance and …
Learning to rank an assortment of products
KJ Ferreira, S Parthasarathy… - Management Science, 2022 - pubsonline.informs.org
We consider the product-ranking challenge that online retailers face when their customers
typically behave as “window shoppers.” They form an impression of the assortment after …
typically behave as “window shoppers.” They form an impression of the assortment after …
On interactive learning-to-rank for IR: Overview, recent advances, challenges, and directions
With the amount and variety of information available on digital repositories, answering
complex user needs and personalizing information access became a hard task. Putting the …
complex user needs and personalizing information access became a hard task. Putting the …
A fast bandit algorithm for recommendation to users with heterogenous tastes
We study recommendation in scenarios where there's no prior information about the quality
of content in the system. We present an online algorithm that continually optimizes …
of content in the system. We present an online algorithm that continually optimizes …
Modeling document novelty with neural tensor network for search result diversification
Search result diversification has attracted considerable attention as a means to tackle the
ambiguous or multi-faceted information needs of users. One of the key problems in search …
ambiguous or multi-faceted information needs of users. One of the key problems in search …