239 Result(s)
-
Chapter and Conference Paper
Leveraging Customer Reviews for E-commerce Query Generation
Customer reviews are an effective source of information about what people deem important in products (e.g. “strong zipper” for tents). These crowd-created descriptors not only highlight key product attributes,...
-
Chapter and Conference Paper
Keyphrase Extraction as Sequence Labeling Using Contextualized Embeddings
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented using deep contextualized embed...
-
Chapter and Conference Paper
Reproducibility is a Process, Not an Achievement: The Replicability of IR Reproducibility Experiments
This paper espouses a view of reproducibility in the computational sciences as a process and not just a point-in-time “achievement”. As a concrete case study, we revisit the Open-Source IR Reproducibility Challen...
-
Chapter and Conference Paper
Early Detection of Rumours on Twitter via Stance Transfer Learning
Rumour detection on Twitter is an important problem. Existing studies mainly focus on high detection accuracy, which often requires large volumes of data on contents, source credibility or propagation. In this...
-
Chapter and Conference Paper
Mixture Modules Based Intelligent Control System for Autonomous Driving
As a typical artificial intelligence system, a safe and comfortable control system is essential for self-driving vehicles to have the same level of driving ability as human drivers. This paper proposes a novel...
-
Chapter and Conference Paper
Modeling Heterogeneous Influences for Point-of-Interest Recommendation in Location-Based Social Networks
The huge amount of heterogeneous information in location-based social networks (LBSNs) creates great challenges for POI recommendation. User check-in behavior exhibits two properties, diversity and imbalance. To ...
-
Chapter and Conference Paper
Deep Learning-Based Sequential Recommender Systems: Concepts, Algorithms, and Evaluations
What is sequential recommendation? What challenges are traditional sequential recommendation models facing? How to address these challenges in sequential recommendation using advanced deep learning (DL) techni...
-
Chapter and Conference Paper
Finding Baby Mothers on Twitter
In this paper, we study the task of detecting mothers of babies on Twitter. This could be beneficial for baby mother users to find friends, and for companies, organizations or experts to deliver accurately tar...
-
Chapter and Conference Paper
An Automatic Data Service Generation Approach for Cross-origin Datasets
As a unified data access model, data service has become a promising technique to integrate and share heterogeneous datasets. In order to publish overwhelming data on the web, it is a key to automatically extra...
-
Chapter and Conference Paper
Extracting Action Sensitive Features to Facilitate Weakly-Supervised Action Localization
Weakly-supervised temporal action localization has attracted much attention among researchers in video content analytics, thanks to its relaxed requirements of video-level annotations instead of frame-level la...
-
Chapter and Conference Paper
Supervised Group Embedding for Rumor Detection in Social Media
To detect rumors automatically in social media, methods based on recurrent neural network and convolutional neural network have been proposed. These methods split a stream of posts related to an event into sev...
-
Chapter and Conference Paper
Knowledge-Based Short Text Categorization Using Entity and Category Embedding
Short text categorization is an important task due to the rapid growth of online available short texts in various domains such as web search snippets, etc. Most of the traditional methods suffer from sparsity ...
-
Chapter and Conference Paper
Time and Location Recommendation for Crime Prevention
In recent years we have seen more and more open government and administrative data made available on the Web. Crime data, for example, allows civic organizations and ordinary citizens to obtain safety-related ...
-
Chapter and Conference Paper
PARMTRD: Parallel Association Rules Based Multiple-Topic Relationships Detection
Lots of events happened everyday make social big data have plenty of topics. A topic usually comprises a series of stories. Clues of associations among stories are usually clear, but hidden associations among ...
-
Chapter and Conference Paper
Hate Speech Detection on Twitter: Feature Engineering v.s. Feature Selection
The increasing presence of hate speech on social media has drawn significant investment from governments, companies, and empirical research. Existing methods typically use a supervised text classification appr...
-
Chapter and Conference Paper
Classifying Quality Centrality for Source Localization in Social Networks
Source localization, the process of estimating the originator of an epidemic outbreak or rumor propagation in a network, is an important issue in epidemiology and sociology. With the graph topology of the unde...
-
Chapter and Conference Paper
Big Social Data as a Service: A Service Composition Framework for Social Information Service Analysis
We propose a ‘Big Social Data as a Service’ (BSDaaS) composition framework that extracts the data from social information services, and transforms it into useful information. We propose a novel service quality...
-
Chapter and Conference Paper
Refining Traceability Links Between Vulnerability and Software Component in a Vulnerability Knowledge Graph
Software vulnerabilities and their corresponding software components information are usually stored in different locations with different representations. Building accurate traceability links between them to f...
-
Chapter and Conference Paper
Detecting Hate Speech on Twitter Using a Convolution-GRU Based Deep Neural Network
In recent years, the increasing propagation of hate speech on social media and the urgent need for effective counter-measures have drawn significant investment from governments, companies, and empirical resear...
-
Chapter and Conference Paper
Coupled Linear and Deep Nonlinear Method for Meetup Service Recommendation
Meetup brings people with similar interests together to do things that matter to them. For example, it provides a platform for getting people who love hiking, coding, running marathons, learning foreign langua...