SECTION: Original Papers

Open Access
Scalable Representation Learning for Dynamic Heterogeneous Information Networks via Metagraphs
October 2022, Article No.: 64, pp 1–27

Content representation is a fundamental task in information retrieval. Representation learning is aimed at capturing features of an information object in a low-dimensional space. Most research on representation learning for heterogeneous information ...

STARec: Adaptive Learning with Spatiotemporal and Activity Influence for POI Recommendation
October 2022, Article No.: 65, pp 1–40

POI recommendation has become an essential means to help people discover attractive places. Intuitively, activities have an important impact on users’ decision-making, because users select POIs to attend corresponding activities. However, many existing ...

Graph Co-Attentive Session-based Recommendation
October 2022, Article No.: 67, pp 1–31

Session-based recommendation aims to generate recommendations merely based on the ongoing session, which is a challenging task. Previous methods mainly focus on modeling the sequential signals or the transition relations between items in the current ...

Grounded Task Prioritization with Context-Aware Sequential Ranking
October 2022, Article No.: 68, pp 1–28

People rely on task management applications and digital assistants to capture and track their tasks, and help with executing them. The burden of organizing and scheduling time for tasks continues to reside with users of these systems, despite the high ...

Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks
October 2022, Article No.: 69, pp 1–46

Graph Neural Networks (GNNs) have been widely used for the representation learning of various structured graph data, typically through message passing among nodes by aggregating their neighborhood information via different operations. While promising, ...

Personalized and Explainable Employee Training Course Recommendations: A Bayesian Variational Approach
October 2022, Article No.: 70, pp 1–32

As a major component of strategic talent management, learning and development (L&D) aims at improving the individual and organization performances through planning tailored training for employees to increase and improve their skills and knowledge. While ...

The Footprint of Factorization Models and Their Applications in Collaborative Filtering
October 2022, Article No.: 71, pp 1–32

Factorization models have been successfully applied to the recommendation problems and have significant impact to both academia and industries in the field of Collaborative Filtering (CF). However, the intermediate data generated in factorization models’ ...

Combining Graph Convolutional Neural Networks and Label Propagation
October 2022, Article No.: 73, pp 1–27

Label Propagation Algorithm (LPA) and Graph Convolutional Neural Networks (GCN) are both message passing algorithms on graphs. Both solve the task of node classification, but LPA propagates node label information across the edges of the graph, while GCN ...

Learning Text-image Joint Embedding for Efficient Cross-modal Retrieval with Deep Feature Engineering
October 2022, Article No.: 74, pp 1–27

This article introduces a two-phase deep feature engineering framework for efficient learning of semantics enhanced joint embedding, which clearly separates the deep feature engineering in data preprocessing from training the text-image joint embedding ...

Feature-Level Attentive ICF for Recommendation
October 2022, Article No.: 75, pp 1–24

Item-based collaborative filtering (ICF) enjoys the advantages of high recommendation accuracy and ease in online penalization and thus is favored by the industrial recommender systems. ICF recommends items to a target user based on their similarities to ...

Open Access
Relevance Assessments for Web Search Evaluation: Should We Randomise or Prioritise the Pooled Documents?
October 2022, Article No.: 76, pp 1–35

In the context of depth-k pooling for constructing web search test collections, we compare two approaches to ordering pooled documents for relevance assessors: The prioritisation strategy (PRI) used widely at NTCIR, and the simple randomisation strategy (...

Understanding the “Pathway” Towards a Searcher’s Learning Objective
October 2022, Article No.: 77, pp 1–42

Search systems are often used to support learning-oriented goals. This trend has given rise to the “search-as-learning” movement, which proposes that search systems should be designed to support learning. To this end, an important research question is: ...

Scaling High-Quality Pairwise Link-Based Similarity Retrieval on Billion-Edge Graphs
October 2022, Article No.: 78, pp 1–45

SimRank is an attractive link-based similarity measure used in fertile fields of Web search and sociometry. However, the existing deterministic method by Kusumoto et al. [24] for retrieving SimRank does not always produce high-quality similarity results, ...

Jointly Predicting Future Content in Multiple Social Media Sites Based on Multi-task Learning
October 2022, Article No.: 79, pp 1–28

User-generated contents (UGC) in social media are the direct expression of users’ interests, preferences, and opinions. User behavior prediction based on UGC has increasingly been investigated in recent years. Compared to learning a person’s behavioral ...

A Re-classification of Information Seeking Tasks and Their Computational Solutions
October 2022, Article No.: 80, pp 1–32

This article presents a re-classification of information seeking (IS) tasks, concepts, and algorithms. The proposed taxonomy provides new dimensions to look into information seeking tasks and methods. The new dimensions include number of search iterations,...

Open Access
“What Can I Cook with these Ingredients?” - Understanding Cooking-Related Information Needs in Conversational Search
October 2022, Article No.: 81, pp 1–32

As conversational search becomes more pervasive, it becomes increasingly important to understand the users’ underlying information needs when they converse with such systems in diverse domains. We conduct an in situ study to understand information needs ...

Dynamic Graph Reasoning for Conversational Open-Domain Question Answering
October 2022, Article No.: 82, pp 1–24

In recent years, conversational agents have provided a natural and convenient access to useful information in people’s daily life, along with a broad and new research topic, conversational question answering (QA). On the shoulders of conversational QA, we ...

MiDTD: A Simple and Effective Distillation Framework for Distantly Supervised Relation Extraction
October 2022, Article No.: 83, pp 1–32

Relation extraction (RE), an important information extraction task, faced the great challenge brought by limited annotation data. To this end, distant supervision was proposed to automatically label RE data, and thus largely increased the number of ...

Complex-valued Neural Network-based Quantum Language Models
October 2022, Article No.: 84, pp 1–31

Language modeling is essential in Natural Language Processing and Information Retrieval related tasks. After the statistical language models, Quantum Language Model (QLM) has been proposed to unify both single words and compound terms in the same ...

Leveraging Narrative to Generate Movie Script
October 2022, Article No.: 86, pp 1–32

Generating a text based on a predefined guideline is an interesting but challenging problem. A series of studies have been carried out in recent years. In dialogue systems, researchers have explored driving a dialogue based on a plan, while in story ...

Toward Personalized Answer Generation in E-Commerce via Multi-perspective Preference Modeling
October 2022, Article No.: 87, pp 1–28

Recently, Product Question Answering (PQA) on E-Commerce platforms has attracted increasing attention as it can act as an intelligent online shopping assistant and improve the customer shopping experience. Its key function, automatic answer generation for ...

A Systematic Analysis on the Impact of Contextual Information on Point-of-Interest Recommendation
October 2022, Article No.: 88, pp 1–35

As the popularity of Location-based Social Networks increases, designing accurate models for Point-of-Interest (POI) recommendation receives more attention. POI recommendation is often performed by incorporating contextual information into previously ...



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