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Towards Effective and Efficient Sparse Neural Information Retrieval

Sparse representation learning based on Pre-trained Language Models has seen a growing interest in Information Retrieval. Such approaches can take advantage of the proven efficiency of inverted indexes, and inherit desirable IR priors such as …

On the Study of Transformers for Query Suggestion

When conducting a search task, users may find it difficult to articulate their need, even more so when the task is complex. To help them complete their search, search engine usually provide query suggestions. A good query suggestion system requires …

Representation Learning for Classification in Heterogeneous Graphs with Application to Social Networks

We address the task of node classification in heterogeneous networks, where the nodes are of different types, each type having its own set of labels, and the relations between nodes may also be of different types. A typical example is provided by …

Evolutionary optimization of convolutional neural networks for cancer miRNA biomarkers classification

Cancer diagnosis is currently undergoing a paradigm shift with the incorporation of molecular biomarkers as part of routine diagnostic panel. This breakthrough discovery directs researches to examine the role of microRNA in cancer, since its …

Model Based Comparison of Discounted Cumulative Gain and Average Precision

On using a quantum physics formalism for multidocument summarization

Introduction to the special issue on Graphical Models and Information Retrieval

Sound and Complete Relevance Assessments for XML Retrieval

An Extension of Precision-Recall with User Modelling (PRUM): Application to XML Retrieval