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Two Decades of Network Science as seen through the co-authorship network of network scientistsAug 22 2019Complex networks have attracted a great deal of research interest in the last two decades since Watts & Strogatz, Barab\'asi & Albert and Girvan & Newman published their highly-cited seminal papers on small-world networks, on scale-free networks and on ... More
Measuring the Business Value of Recommender SystemsAug 22 2019Recommender Systems are nowadays successfully used by all major web sites (from e-commerce to social media) to filter content and make suggestions in a personalized way. Academic research largely focuses on the value of recommenders for consumers, e.g., ... More
Session-based Complementary Fashion RecommendationsAug 22 2019In modern fashion e-commerce platforms, where customers can browse thousands to millions of products, recommender systems are useful tools to navigate and narrow down the vast assortment. In this scenario, complementary recommendations serve the user ... More
Using Social Media for Word-of-Mouth MarketingAug 22 2019Nowadays online social networks are used extensively for personal and commercial purposes. This widespread popularity makes them an ideal platform for advertisements. Social media can be used for both direct and word-of-mouth (WoM) marketing. Although ... More
Two-Stage Session-based Recommendations with Candidate Rank EmbeddingsAug 22 2019Recent advances in Session-based recommender systems have gained attention due to their potential of providing real-time personalized recommendations with high recall, especially when compared to traditional methods like matrix factorization and item-based ... More
Sentiment Dynamics in Social Media News ChannelsAug 21 2019Social media is currently one of the most important means of news communication. Since people are consuming a large fraction of their daily news through social media, most of the traditional news channels are using social media to catch the attention ... More
Assessing the Impact of a User-Item Collaborative Attack on Class of UsersAug 21 2019Collaborative Filtering (CF) models lie at the core of most recommendation systems due to their state-of-the-art accuracy. They are commonly adopted in e-commerce and online services for their impact on sales volume and/or diversity, and their impact ... More
Boosting the Rating Prediction with Click Data and Textual ContentsAug 21 2019Matrix factorization (MF) is one of the most efficient methods for rating predictions. MF learns user and item representations by factorizing the user-item rating matrix. Further, textual contents are integrated to conventional MF to address the cold-start ... More
User Diverse Preference Modeling by Multimodal Attentive Metric LearningAug 21 2019Most existing recommender systems represent a user's preference with a feature vector, which is assumed to be fixed when predicting this user's preferences for different items. However, the same vector cannot accurately capture a user's varying preferences ... More
Hebbian Graph EmbeddingsAug 21 2019Representation learning has recently been successfully used to create vector representations of entities in language learning, recommender systems and in similarity learning. Graph embeddings exploit the locality structure of a graph and generate embeddings ... More
Learning Joint Embedding for Cross-Modal RetrievalAug 21 2019A cross-modal retrieval process is to use a query in one modality to obtain relevant data in another modality. The challenging issue of cross-modal retrieval lies in bridging the heterogeneous gap for similarity computation, which has been broadly discussed ... More
Personalizing Search Results Using Hierarchical RNN with Query-aware AttentionAug 20 2019Search results personalization has become an effective way to improve the quality of search engines. Previous studies extracted information such as past clicks, user topical interests, query click entropy and so on to tailor the original ranking. However, ... More
From Text to Sound: A Preliminary Study on Retrieving Sound Effects to Radio StoriesAug 20 2019Sound effects play an essential role in producing high-quality radio stories but require enormous labor cost to add. In this paper, we address the problem of automatically adding sound effects to radio stories with a retrieval-based model. However, directly ... More
ViSiL: Fine-grained Spatio-Temporal Video Similarity LearningAug 20 2019In this paper we introduce ViSiL, a Video Similarity Learning architecture that considers fine-grained Spatio-Temporal relations between pairs of videos -- such relations are typically lost in previous video retrieval approaches that embed the whole frame ... More
Hierarchical Bayesian Personalized Recommendation: A Case Study and BeyondAug 20 2019Items in modern recommender systems are often organized in hierarchical structures. These hierarchical structures and the data within them provide valuable information for building personalized recommendation systems. In this paper, we propose a general ... More
Unsupervised Hierarchical Grouping of Knowledge Graph EntitiesAug 20 2019Knowledge graphs have attracted lots of attention in academic and industrial environments. Despite their usefulness, popular knowledge graphs suffer from incompleteness of information, especially in their type assertions. This has encouraged research ... More
CatE: Category-Name GuidedWord EmbeddingAug 20 2019Unsupervised word embedding has benefited a wide spectrum of NLP tasks due to its effectiveness of encoding word semantics in distributed word representations. However, unsupervised word embedding is a generic representation, not optimized for specific ... More
Estimating Attention Flow in Online Video NetworkAug 20 2019Online videos have shown tremendous increase in Internet traffic. Most video hosting sites implement recommender systems, which connect the videos into a directed network and conceptually act as a source of pathways for users to navigate. At present, ... More
SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view GraphsAug 19 2019Aug 21 2019Given the reach of web platforms, bad actors have considerable incentives to manipulate and defraud users at the expense of platform integrity. This has spurred research in numerous suspicious behavior detection tasks, including detection of sybil accounts, ... More
Tale of tails using rule augmented sequence labeling for event extractionAug 19 2019The problem of event extraction is a relatively difficult task for low resource languages due to the non-availability of sufficient annotated data. Moreover, the task becomes complex for tail (rarely occurring) labels wherein extremely less data is available. ... More
Message Passing for Complex Question Answering over Knowledge GraphsAug 19 2019Question answering over knowledge graphs (KGQA) has evolved from simple single-fact questions to complex questions that require graph traversal and aggregation. We propose a novel approach for complex KGQA that uses unsupervised message passing, which ... More
Relevance Proximity Graphs for Fast Relevance RetrievalAug 19 2019In plenty of machine learning applications, the most relevant items for a particular query should be efficiently extracted, while the relevance function is based on a highly-nonlinear model, e.g., DNNs or GBDTs. Due to the high computational complexity ... More
Relevance Proximity Graphs for Fast Relevance RetrievalAug 19 2019Aug 20 2019In plenty of machine learning applications, the most relevant items for a particular query should be efficiently extracted, while the relevance function is based on a highly-nonlinear model, e.g., DNNs or GBDTs. Due to the high computational complexity ... More
A Study of BERT for Non-Factoid Question-Answering under Passage Length ConstraintsAug 19 2019We study the use of BERT for non-factoid question-answering, focusing on the passage re-ranking task under varying passage lengths. To this end, we explore the fine-tuning of BERT in different learning-to-rank setups, comprising both point-wise and pair-wise ... More
Recommender Systems Fairness Evaluation via Generalized Cross EntropyAug 19 2019Fairness in recommender systems has been considered with respect to sensitive attributes of users (e.g., gender, race) or items (e.g., revenue in a multistakeholder setting). Regardless, the concept has been commonly interpreted as some form of equality ... More
Latent User Linking for Collaborative Cross Domain RecommendationAug 19 2019With the widespread adoption of information systems, recommender systems are widely used for better user experience. Collaborative filtering is a popular approach in implementing recommender systems. Yet, collaborative filtering methods are highly dependent ... More
The Design and Implementation of a Real Time Visual Search System on JD E-commerce PlatformAug 19 2019We present the design and implementation of a visual search system for real time image retrieval on, the world's third largest and China's largest e-commerce site. We demonstrate that our system can support real time visual search with hundreds ... More
A Novel Kalman Filter Based Shilling Attack Detection AlgorithmAug 18 2019Collaborative filtering has been widely used in recommendation systems to recommend items that users might like. However, collaborative filtering based recommendation systems are vulnerable to shilling attacks. Malicious users tend to increase or decrease ... More
Detection of Shilling Attack Based on T-distribution on the Dynamic Time Intervals in Recommendation SystemsAug 18 2019With the development of information technology and the Internet, recommendation systems have become an important means to solve the problem of information overload. However, recommendation system is greatly fragile as it relies heavily on behavior data ... More
Comparison-Based Indexing From First PrinciplesAug 17 2019Basic assumptions about comparison-based indexing are laid down and a general design space is derived from these. An index structure spanning this design space (the sprawl) is described, along with an associated family of partitioning predicates, or regions ... More
Onset detection: A new approach to QBH systemAug 17 2019Query by Humming (QBH) is an system to provide a user with the song(s) which the user hums to the system. Current QBH method requires the extraction of onset and pitch information in order to track similarity with various versions of different songs. ... More
Accelerated learning from recommender systems using multi-armed banditAug 16 2019Recommendation systems are a vital component of many online marketplaces, where there are often millions of items to potentially present to users who have a wide variety of wants or needs. Evaluating recommender system algorithms is a hard task, given ... More
Shallow Domain Adaptive Embeddings for Sentiment AnalysisAug 16 2019This paper proposes a way to improve the performance of existing algorithms for text classification in domains with strong language semantics. We propose a domain adaptation layer learns weights to combine a generic and a domain specific (DS) word embedding ... More
Learning Representations and Agents for Information RetrievalAug 16 2019A goal shared by artificial intelligence and information retrieval is to create an oracle, that is, a machine that can answer our questions, no matter how difficult they are. A more limited, but still instrumental, version of this oracle is a question-answering ... More
CFO: A Framework for Building Production NLP SystemsAug 16 2019This paper introduces a novel orchestration framework, called CFO (COMPUTATION FLOW ORCHESTRATOR), for building, experimenting with, and deploying interactive NLP (Natural Language Processing) and IR (Information Retrieval) systems to production environments. ... More
CommentsRadar: Dive into Unique Data on All Comments on the WebAug 16 2019We introduce an entity-centric search engineCommentsRadarthatpairs entity queries with articles and user opinions covering a widerange of topics from top commented sites. The engine aggregatesarticles and comments for these articles, extracts named entities,links ... More
Do Co-purchases Reveal Preferences? Explainable Recommendation with Attribute NetworksAug 16 2019With the prosperity of business intelligence, recommender systems have evolved into a new stage that we not only care about what to recommend, but why it is recommended. Explainability of recommendations thus emerges as a focal point of research and becomes ... More
Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic ReviewAug 15 2019Of the 2652 articles considered, 106 met the inclusion criteria. Review of the included papers resulted in identification of 43 chronic diseases, which were then further classified into 10 disease categories using ICD-10. The majority of studies focused ... More
On Gossip-based Information Dissemination in Pervasive Recommender SystemsAug 15 2019Pervasive computing systems employ distributed and embedded devices in order to raise, communicate, and process data in an anytime-anywhere fashion. Certainly, its most prominent device is the smartphone due to its wide proliferation, growing computation ... More
Hamming Sentence Embeddings for Information RetrievalAug 15 2019In retrieval applications, binary hashes are known to offer significant improvements in terms of both memory and speed. We investigate the compression of sentence embeddings using a neural encoder-decoder architecture, which is trained by minimizing reconstruction ... More
Temporal Collaborative Ranking Via Personalized TransformerAug 15 2019The collaborative ranking problem has been an important open research question as most recommendation problems can be naturally formulated as ranking problems. While much of collaborative ranking methodology assumes static ranking data, the importance ... More
Towards Knowledge-Based Recommender Dialog SystemAug 15 2019In this paper, we propose a novel end-to-end framework called KBRD, which stands for Knowledge-Based Recommender Dialog System. It integrates the recommender system and the dialog generation system. The dialog system can enhance the performance of the ... More
Two-stage Federated Phenotyping and Patient Representation LearningAug 14 2019A large percentage of medical information is in unstructured text format in electronic medical record systems. Manual extraction of information from clinical notes is extremely time consuming. Natural language processing has been widely used in recent ... More
Towards Optimisation of Collaborative Question Answering over Knowledge GraphsAug 14 2019Collaborative Question Answering (CQA) frameworks for knowledge graphs aim at integrating existing question answering (QA) components for implementing sequences of QA tasks (i.e. QA pipelines). The research community has paid substantial attention to ... More
Harmonized Multimodal Learning with Gaussian Process Latent Variable ModelsAug 14 2019Multimodal learning aims to discover the relationship between multiple modalities. It has become an important research topic due to extensive multimodal applications such as cross-modal retrieval. This paper attempts to address the modality heterogeneity ... More
Complicated Table Structure RecognitionAug 13 2019The task of table structure recognition aims to recognize the internal structure of a table, which is a key step to make machines understand tables. Currently, there are lots of studies on this task for different file formats such as ASCII text and HTML. ... More
FCNHSMRA_HRS: Improve the performance of the movie hybrid recommender system using resource allocation approachAug 13 2019Recommender systems are systems that are capable of offering the most suitable services and products to users. Through specific methods and techniques, the recommender systems try to identify the most appropriate items, such as types of information and ... More
CUPCF: Combining Users Preferences in Collaborative Filtering for Better RecommendationAug 13 2019How to make the best decision between the opinions and tastes of your friends and acquaintances? Therefore, recommender systems are used to solve such issues. The common algorithms use a similarity measure to predict active users' tastes over a particular ... More
Evaluation of a Recommender System for Assisting Novice Game DesignersAug 13 2019Game development is a complex task involving multiple disciplines and technologies. Developers and researchers alike have suggested that AI-driven game design assistants may improve developer workflow. We present a recommender system for assisting humans ... More
Learning Credible Deep Neural Networks with Rationale RegularizationAug 13 2019Recent explainability related studies have shown that state-of-the-art DNNs do not always adopt correct evidences to make decisions. It not only hampers their generalization but also makes them less likely to be trusted by end-users. In pursuit of developing ... More
GraphSW: a training protocol based on stage-wise training for GNN-based Recommender ModelAug 13 2019Aug 19 2019Recently, researchers utilize Knowledge Graph (KG) as side information in recommendation system to address cold start and sparsity issue and improve the recommendation performance. Existing KG-aware recommendation model use the feature of neighboring ... More
Generative Question Refinement with Deep Reinforcement Learning in Retrieval-based QA SystemAug 13 2019In real-world question-answering (QA) systems, ill-formed questions, such as wrong words, ill word order, and noisy expressions, are common and may prevent the QA systems from understanding and answering them accurately. In order to eliminate the effect ... More
Exploiting Multi-domain Visual Information for Fake News DetectionAug 13 2019The increasing popularity of social media promotes the proliferation of fake news. With the development of multimedia technology, fake news attempts to utilize multimedia contents with images or videos to attract and mislead readers for rapid dissemination, ... More
Linking Graph Entities with Multiplicity and ProvenanceAug 13 2019Entity linking is a fundamental database problem with applicationsin data integration, data cleansing, information retrieval, knowledge fusion, and knowledge-base population. It is the task of accurately identifying multiple, differing, and possibly contradictingrepresentations ... More
AmazonQA: A Review-Based Question Answering TaskAug 12 2019Aug 20 2019Every day, thousands of customers post questions on Amazon product pages. After some time, if they are fortunate, a knowledgeable customer might answer their question. Observing that many questions can be answered based upon the available product reviews, ... More
AmazonQA: A Review-Based Question Answering TaskAug 12 2019Every day, thousands of customers post questions on Amazon product pages. After some time, if they are fortunate, a knowledgeable customer might answer their question. Observing that many questions can be answered based upon the available product reviews, ... More
Assessing the Quality of Scientific PapersAug 12 2019A multitude of factors are responsible for the overall quality of scientific papers, including readability, linguistic quality, fluency,semantic complexity, and of course domain-specific technical factors. These factors vary from one field of study to ... More
SHREWD: Semantic Hierarchy-based Relational Embeddings for Weakly-supervised Deep HashingAug 12 2019Using class labels to represent class similarity is a typical approach to training deep hashing systems for retrieval; samples from the same or different classes take binary 1 or 0 similarity values. This similarity does not model the full rich knowledge ... More
Automatic Fashion Knowledge Extraction from Social MediaAug 12 2019Fashion knowledge plays a pivotal role in helping people in their dressing. In this paper, we present a novel system to automatically harvest fashion knowledge from social media. It unifies three tasks of occasion, person and clothing discovery from multiple ... More
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity MetricAug 12 2019In this paper, we present our work to support publishers and editors in finding descriptive tags for e-books through tag recommendations. We propose a hybrid tag recommendation system for e-books, which leverages search query terms from Amazon users and ... More
An End-to-End Neighborhood-based Interaction Model forKnowledge-enhanced RecommendationAug 12 2019This paper studies graph-based recommendation, where an interaction graph is constructed built from historical records and is lever-aged to alleviate data sparsity and cold start problems. We reveal an early summarization problem in existing graph-based ... More
Using the Open Meta Kaggle Dataset to Evaluate Tripartite Recommendations in Data MarketsAug 12 2019This work addresses the problem of providing and evaluating recommendations in data markets. Since most of the research in recommender systems is focused on the bipartite relationship between users and items (e.g., movies), we extend this view to the ... More
Tensor Factorization with Label Information for Fake News DetectionAug 11 2019The buzz over the so-called "fake news" has created concerns about a degenerated media environment and led to the need for technological solutions. As the detection of fake news is increasingly considered a technological problem, it has attracted considerable ... More
Exploiting Temporal Relationships in Video Moment Localization with Natural LanguageAug 11 2019We address the problem of video moment localization with natural language, i.e. localizing a video segment described by a natural language sentence. While most prior work focuses on grounding the query as a whole, temporal dependencies and reasoning between ... More
Exploring the Effect of an Item's Neighborhood on its Sellability in eCommerceAug 10 2019Predicting the sale of an item is a critical problem in eCommerce search. Typically, items are independently predicted with a probability of sale for a given search query. But in a dynamic marketplace like eBay, even for a single product, there are various ... More
Audio-Visual Embedding for Cross-Modal MusicVideo Retrieval through Supervised Deep CCAAug 10 2019Deep learning has successfully shown excellent performance in learning joint representations between different data modalities. Unfortunately, little research focuses on cross-modal correlation learning where temporal structures of different data modalities, ... More
Personalized Music Recommendation with Triplet NetworkAug 10 2019Since many online music services emerged in recent years so that effective music recommendation systems are desirable. Some common problems in recommendation system like feature representations, distance measure and cold start problems are also challenges ... More
Deep Triplet Neural Networks with Cluster-CCA for Audio-Visual Cross-modal RetrievalAug 10 2019Cross-modal retrieval aims to retrieve data in one modality by a query in another modality, which has been avery interesting research issue in the filed of multimedia, information retrieval, and computer vision, anddatabase. Most existing works focus ... More
TEQUILA: Temporal Question Answering over Knowledge BasesAug 09 2019Question answering over knowledge bases (KB-QA) poses challenges in handling complex questions that need to be decomposed into sub-questions. An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be ... More
TEQUILA: Temporal Question Answering over Knowledge BasesAug 09 2019Aug 15 2019Question answering over knowledge bases (KB-QA) poses challenges in handling complex questions that need to be decomposed into sub-questions. An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be ... More
BERT-based Ranking for Biomedical Entity NormalizationAug 09 2019Developing high-performance entity normalization algorithms that can alleviate the term variation problem is of great interest to the biomedical community. Although deep learning-based methods have been successfully applied to biomedical entity normalization, ... More
Interactive Variance Attention based Online Spoiler Detection for Time-Sync CommentsAug 09 2019Nowadays, time-sync comment (TSC), a new form of interactive comments, has become increasingly popular in Chinese video websites. By posting TSCs, people can easily express their feelings and exchange their opinions with others when watching online videos. ... More
Interactive Variance Attention based Online Spoiler Detection for Time-Sync CommentsAug 09 2019Aug 21 2019Nowadays, time-sync comment (TSC), a new form of interactive comments, has become increasingly popular in Chinese video websites. By posting TSCs, people can easily express their feelings and exchange their opinions with others when watching online videos. ... More
Enhancing Flood Impact Analysis using Interactive Retrieval of Social Media ImagesAug 09 2019The analysis of natural disasters such as floods in a timely manner often suffers from limited data due to a coarse distribution of sensors or sensor failures. This limitation could be alleviated by leveraging information contained in images of the event ... More
Using Semantic Role Knowledge for Relevance Ranking of Key Phrases in Documents: An Unsupervised ApproachAug 09 2019In this paper, we investigate the integration of sentence position and semantic role of words in a PageRank system to build a key phrase ranking method. We present the evaluation results of our approach on three scientific articles. We show that semantic ... More
A Simple Recommender Engine for Matching Final-Year Project Student with SupervisorAug 08 2019This paper discusses a simple recommender engine, which can match final year project student based on their interests with potential supervisors. The recommender engine is constructed based on Euclidean distance algorithm. The initial input data for the ... More
Neural Document Expansion with User FeedbackAug 08 2019This paper presents a neural document expansion approach (NeuDEF) that enriches document representations for neural ranking models. NeuDEF harvests expansion terms from queries which lead to clicks on the document and weights these expansion terms with ... More
Making Recommendations from Web Archives for "Lost" Web PagesAug 07 2019When a user requests a web page from a web archive, the user will typically either get an HTTP 200 if the page is available, or an HTTP 404 if the web page has not been archived. This is because web archives are typically accessed by URI lookup, and the ... More
Exploring the Intersections of Web Science and AccessibilityAug 07 2019The web is the prominent way information is exchanged in the 21st century. However, ensuring web-based information is accessible is complicated, particularly with web applications that rely on JavaScript and other technologies to deliver and build representations; ... More
Hierarchy-of-Visual-Words: a Learning-based Approach for Trademark Image RetrievalAug 07 2019In this paper, we present the Hierarchy-of-Visual-Words (HoVW), a novel trademark image retrieval (TIR) method that decomposes images into simpler geometric shapes and defines a descriptor for binary trademark image representation by encoding the hierarchical ... More
Understanding Optical Music RecognitionAug 07 2019For over 50 years, researchers have been trying to teach computers to read music notation, referred to as Optical Music Recognition (OMR). However, this field is still difficult to access for new researchers, especially those without a significant musical ... More
Understanding Optical Music RecognitionAug 07 2019Aug 14 2019For over 50 years, researchers have been trying to teach computers to read music notation, referred to as Optical Music Recognition (OMR). However, this field is still difficult to access for new researchers, especially those without a significant musical ... More
TinySearch -- Semantics based Search Engine using Bert EmbeddingsAug 07 2019Existing search engines use keyword matching or tf-idf based matching to map the query to the web-documents and rank them. They also consider other factors such as page rank, hubs-and-authority scores, knowledge graphs to make the results more meaningful. ... More
The Hitchhiker's Guide to LDAAug 07 2019Latent Dirichlet Allocation (LDA) model is a famous model in the topic model field, it has been studied for years due to its extensive application value in industry and academia. However, the mathematical derivation of LDA model is challenging and difficult, ... More
Text mining policy: Classifying forest and landscape restoration policy agenda with neural information retrievalAug 07 2019Dozens of countries have committed to restoring the ecological functionality of 350 million hectares of land by 2030. In order to achieve such wide-scale implementation of restoration, the values and priorities of multi-sectoral stakeholders must be aligned ... More
Local versus Global Strategies in Social Query ExpansionAug 05 2019Link sharing in social media can be seen as a collaboratively retrieved set of documents for a query or topic expressed by a hashtag. Temporal information plays an important role for identifying the correct context for which such annotations are valid ... More
Unsupervised Context Retrieval for Long-tail EntitiesAug 05 2019Monitoring entities in media streams often relies on rich entity representations, like structured information available in a knowledge base (KB). For long-tail entities, such monitoring is highly challenging, due to their limited, if not entirely missing, ... More
Performance Evaluation of Supervised Machine Learning Techniques for Efficient Detection of Emotions from Online ContentAug 05 2019Emotion detection from the text is an important and challenging problem in text analytics. The opinion-mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including ... More
Beyond English-only Reading Comprehension: Experiments in Zero-Shot Multilingual Transfer for BulgarianAug 05 2019Recently, reading comprehension models achieved near-human performance on large-scale datasets such as SQuAD, CoQA, MS Macro, RACE, etc. This is largely due to the release of pre-trained contextualized representations such as BERT and ELMo, which can ... More
A Fast Content-Based Image Retrieval Method Using Deep Visual FeaturesAug 05 2019Fast and scalable Content-Based Image Retrieval using visual features is required for document analysis, Medical image analysis, etc. in the present age. Convolutional Neural Network (CNN) activations as features achieved their outstanding performance ... More
Improving IT Support by Enhancing Incident Management Process with Multi-modal AnalysisAug 04 2019IT support services industry is going through a major transformation with AI becoming commonplace. There has been a lot of effort in the direction of automation at every human touchpoint in the IT support processes. Incident management is one such process ... More
Behavior Pattern and Compiled Information Based Performance Prediction in MOOCsAug 04 2019With the development of MOOCs massive open online courses, increasingly more subjects can be studied online. Researchers currently show growing interest in the field of MOOCs, including dropout prediction, cheating detection and achievement prediction. ... More
CARL: Aggregated Search with Context-Aware Module Embedding LearningAug 03 2019Aggregated search aims to construct search result pages (SERPs) from blue-links and heterogeneous modules (such as news, images, and videos). Existing studies have largely ignored the correlations between blue-links and heterogeneous modules when selecting ... More
MMF: Attribute Interpretable Collaborative FilteringAug 03 2019Collaborative filtering is one of the most popular techniques in designing recommendation systems, and its most representative model, matrix factorization, has been wildly used by researchers and the industry. However, this model suffers from the lack ... More
RuleKit: A Comprehensive Suite for Rule-Based LearningAug 02 2019Rule-based models are often used for data analysis as they combine interpretability with predictive power. We present RuleKit, a versatile tool for rule learning. Based on a sequential covering induction algorithm, it is suitable for classification, regression, ... More
Bias Disparity in Collaborative Recommendation: Algorithmic Evaluation and ComparisonAug 02 2019Research on fairness in machine learning has been recently extended to recommender systems. One of the factors that may impact fairness is bias disparity, the degree to which a group's preferences on various item categories fail to be reflected in the ... More
On the Merge of k-NN GraphAug 02 2019Aug 06 2019K-nearest neighbor graph is the fundamental data structure in many disciplines such as information retrieval, data-mining, pattern recognition and machine learning, etc. In the literature, considerable research has been focusing on how to efficiently ... More
On the Merge of k-NN GraphAug 02 2019K-nearest neighbor graph is the fundamental data structure in many disciplines such as information retrieval, data-mining, pattern recognition and machine learning, etc. In the literature, considerable research has been focusing on how to efficiently ... More
The Impact of Time on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation ApproachAug 02 2019In our work [KPL17], we study temporal usage patterns of Twitter hashtags, and we use the Base-Level Learning (BLL) equation from the cognitive architecture ACT-R [An04] to model how a person reuses her own, individual hashtags as well as hashtags from ... More
Contrastive Reasons Detection and Clustering from Online Polarized DebateAug 01 2019This work tackles the problem of unsupervised modeling and extraction of the main contrastive sentential reasons conveyed by divergent viewpoints on polarized issues. It proposes a pipeline approach centered around the detection and clustering of phrases, ... More