Abstract Context: Effort-Aware Defect Prediction (EADP) ranks software modules or changes
based on their predicted number of defects (ie, considering modules or changes as effort) or …

This paper proposes K-NRM, a kernel based neural model for document ranking. Given a
query and a set of documents, K-NRM uses a translation matrix that models word-level …

This paper presents\textttConv-KNRM, a Convolutional Kernel-based Neural Ranking Model
that models n-gram soft matches for ad-hoc search. Instead of exact matching query and …

During sudden onset crisis events, the presence of spam, rumors and fake content on Twitter
reduces the value of information contained on its messages (or “tweets”). A possible solution …

The Web has grown into one of the most important channels to communicate social events
nowadays. However, the sheer volume of events available in event-based social networks …

How to optimize ranking metrics such as Normalized Discounted Cumulative Gain (NDCG)
is an important but challenging problem, because ranking metrics are either flat or …

As information retrieval researchers, we not only develop algorithmic solutions to hard
problems, but we also insist on a proper, multifaceted evaluation of ideas. The literature on …

With the development of the Semantic Web, a lot of new structured data has become
available on the Web in the form of knowledge bases (KBs). Making this valuable data …

This paper presents the Entity-Duet Neural Ranking Model (EDRM), which introduces
knowledge graphs to neural search systems. EDRM represents queries and documents by …

Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other
networking sites, the social media shared by users and the associated metadata are …