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View article: Measuring multi-calibration
Measuring multi-calibration Open
A suitable scalar metric can help measure multi-calibration, defined as follows. When the expected values of observed responses are equal to corresponding predicted probabilities, the probabilistic predictions are known as "perfectly calib…
View article: Creating an Intelligent Social Media Campaign Decision-Support Method
Creating an Intelligent Social Media Campaign Decision-Support Method Open
Predicting the success of marketing campaigns on social media can help improve campaign managers' decision-making (e.g., deciding to stop a marketing campaign) and thus increase their profits. Most research in the field of online marketing…
View article: Automated Category Tree Construction: Hardness Bounds and Algorithms
Automated Category Tree Construction: Hardness Bounds and Algorithms Open
Category trees, or taxonomies, are rooted trees where each node, called a category, corresponds to a set of related items. The construction of taxonomies has been studied in various domains, including e-commerce, document management, and q…
View article: TCE: A Test-Based Approach to Measuring Calibration Error
TCE: A Test-Based Approach to Measuring Calibration Error Open
This paper proposes a new metric to measure the calibration error of probabilistic binary classifiers, called test-based calibration error (TCE). TCE incorporates a novel loss function based on a statistical test to examine the extent to w…
View article: Promoting Tail Item Recommendations in E-Commerce
Promoting Tail Item Recommendations in E-Commerce Open
The research area of recommender systems (RS) in e-commerce has become extremely popular in recent years. However, traditional RSs tend to recommend popular items, while niche (long-tail) items are often neglected, which is known as the lo…
View article: Explaining Predictive Uncertainty with Information Theoretic Shapley Values
Explaining Predictive Uncertainty with Information Theoretic Shapley Values Open
Researchers in explainable artificial intelligence have developed numerous methods for helping users understand the predictions of complex supervised learning models. By contrast, explaining the $\textit{uncertainty}$ of model outputs has …
View article: Learning to Rank Articles for Molecular Queries
Learning to Rank Articles for Molecular Queries Open
The cost of developing new drugs is estimated at billions of dollars per year. Identification of new molecules for drugs involves scanning existing bio-medical literature for relevant information. As the potential drug molecule is novel, r…
View article: tBDFS: Temporal Graph Neural Network Leveraging DFS
tBDFS: Temporal Graph Neural Network Leveraging DFS Open
Temporal graph neural networks (temporal GNNs) have been widely researched, reaching state-of-the-art results on multiple prediction tasks. A common approach employed by most previous works is to apply a layer that aggregates information f…
View article: Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly
Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly Open
Consumer demand forecasting is of high importance for many e-commerce\napplications, including supply chain optimization, advertisement placement, and\ndelivery speed optimization. However, reliable time series sales forecasting\nfor e-com…
View article: Lot or Not: Identifying Multi-Quantity Offerings in E-Commerce
Lot or Not: Identifying Multi-Quantity Offerings in E-Commerce Open
The term lot in is defined to mean an offering that contains a collection of multiple identical items for sale. In a large online marketplace, lot offerings play an important role, allowing buyers and sellers to set price levels to optimal…
View article: Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce
Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce Open
In e-commerce, the watchlist enables users to track items over time and has emerged as a primary feature, playing an important role in users' shopping journey. Watchlist items typically have multiple attributes whose values may change over…
View article: E-Commerce Dispute Resolution Prediction
E-Commerce Dispute Resolution Prediction Open
E-Commerce marketplaces support millions of daily transactions, and some disagreements between buyers and sellers are unavoidable. Resolving disputes in an accurate, fast, and fair manner is of great importance for maintaining a trustworth…
View article: Time Masking for Temporal Language Models
Time Masking for Temporal Language Models Open
Our world is constantly evolving, and so is the content on the web. Consequently, our languages, often said to mirror the world, are dynamic in nature. However, most current contextual language models are static and cannot adapt to changes…
View article: Unearthing People from the SaND: Relationship Discovery with Social Media in the Enterprise
Unearthing People from the SaND: Relationship Discovery with Social Media in the Enterprise Open
The popularity of social media across the Internet re- sults in people-centric data sources that users can potentially leverage for relationship discovery tasks. In this paper, we describe SaNDVis, a visual system that supports tasks like …
View article: Event-Driven Query Expansion
Event-Driven Query Expansion Open
A significant number of event-related queries are issued in Web search. In this paper, we seek to improve retrieval performance by leveraging events and specifically target the classic task of query expansion. We propose a method to expand…
View article: E-Commerce Dispute Resolution Prediction
E-Commerce Dispute Resolution Prediction Open
E-Commerce marketplaces support millions of daily transactions, and some\ndisagreements between buyers and sellers are unavoidable. Resolving disputes in\nan accurate, fast, and fair manner is of great importance for maintaining a\ntrustwo…
View article: Node Embedding over Temporal Graphs
Node Embedding over Temporal Graphs Open
In this work, we present a method for node embedding in temporal graphs. We propose an algorithm that learns the evolution of a temporal graph's nodes and edges over time and incorporates this dynamics in a temporal node embedding framewor…
View article: Generating Product Descriptions from User Reviews
Generating Product Descriptions from User Reviews Open
Product descriptions play an important role in the e-commerce ecosystem, conveying to buyers information about a merchandise they may purchase. Yet, on leading e-commerce websites, with high volumes of new items offered for sale every day,…
View article: Beyond Personalization: Research Directions in Multistakeholder Recommendation
Beyond Personalization: Research Directions in Multistakeholder Recommendation Open
Recommender systems are personalized information access applications; they are ubiquitous in today's online environment, and effective at finding items that meet user needs and tastes. As the reach of recommender systems has extended, it h…
View article: Cross-Cultural Transfer Learning for Text Classification
Cross-Cultural Transfer Learning for Text Classification Open
Dor Ringel, Gal Lavee, Ido Guy, Kira Radinsky. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.
View article: Extracting and Ranking Travel Tips from User-Generated Reviews
Extracting and Ranking Travel Tips from User-Generated Reviews Open
User-generated reviews are a key driving force behind some of the leading websites, such as Amazon, TripAdvisor, and Yelp. Yet, the proliferation of user reviews in such sites also poses an information overload challenge: many items, espec…
View article: Fun Facts: Automatic Trivia Fact Extraction from Wikipedia
Fun Facts: Automatic Trivia Fact Extraction from Wikipedia Open
A significant portion of web search queries directly refers to named entities. Search engines explore various ways to improve the user experience for such queries. We suggest augmenting search results with {\em trivia facts} about the sear…