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Articles 2491 - 2520 of 4271
Full-Text Articles in Entire DC Network
Concept-Based Interactive Search System, Yi-Jie Lu, Phuong Anh Nguyen, Hao Zhang, Chong-Wah Ngo
Concept-Based Interactive Search System, Yi-Jie Lu, Phuong Anh Nguyen, Hao Zhang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Our successful multimedia event detection system at TREC-VID 2015 showed its strength on handling complex concepts in a query. The system was based on a large number of pre-trained concept detectors for textual-to-visual relation. In this paper, we enhance the system by enabling human-in-the-loop. In order to facilitate a user to quickly find an information need, we incorporate concept screening, video reranking by highlighted concepts, relevance feedback and color sketch to refine a coarse retrieval result. The aim is to eventually come up with a system suitable for both Ad-hoc Video Search and Known-Item Search. In addition, as the increasing …
Cross-Modal Recipe Retrieval: How To Cook This Dish?, Jingjing Chen, Lei Pang, Chong-Wah Ngo
Cross-Modal Recipe Retrieval: How To Cook This Dish?, Jingjing Chen, Lei Pang, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
In social media users like to share food pictures. One intelligent feature, potentially attractive to amateur chefs, is the recommendation of recipe along with food. Having this feature, unfortunately, is still technically challenging. First, the current technology in food recognition can only scale up to few hundreds of categories, which are yet to be practical for recognizing ten of thousands of food categories. Second, even one food category can have variants of recipes that differ in ingredient composition. Finding the best-match recipe requires knowledge of ingredients, which is a fine-grained recognition problem. In this paper, we consider the problem from …
The Making Of A Successful Analytics Master Degree Program: Experiences And Lessons Drawn For A Young And Small Asian University, Michelle L. F. Cheong
The Making Of A Successful Analytics Master Degree Program: Experiences And Lessons Drawn For A Young And Small Asian University, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Singapore Management University’s School of Information Systems is a young school within a young and small university in Asia. Being young and small, establishing a successful analytics master degree program required extensive landscape research, assessment of its own strengths and weaknesses, having a committed team, and having a clear vision to meet the ever-changing needs of the industry. The Master of IT in Business (Analytics) program, established since 2011, has grown from an annual intake of 16 to 128 students in six years. This article attempts to describe the design process, challenges faced, decisions made, and the key actions taken, …
Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo
Careermapper: An Automated Resume Evaluation Tool, Vivian Lai, Kyong Jin Shim, Richard J. Oentaryo, Philips K. Prasetyo, Casey Vu, Ee-Peng Lim, David Lo
Research Collection School Of Computing and Information Systems
The advent of the Web brought about major changes in the way people search for jobs and companies look for suitable candidates. As more employers and recruitment firms turn to the Web for job candidate search, an increasing number of people turn to the Web for uploading and creating their online resumes. Resumes are often the first source of information about candidates and also the first item of evaluation in candidate selection. Thus, it is imperative that resumes are complete, free of errors and well-organized. We present an automated resume evaluation tool called 'CareerMapper'. Our tool is designed to conduct …
Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang
Cryptographic Reverse Firewall Via Malleable Smooth Projective Hash Functions, Rongmao Chen, Guomin Yang, Guomin Yang, Willy Susilo, Fuchun Guo, Mingwu Zhang
Research Collection School Of Computing and Information Systems
Motivated by the revelations of Edward Snowden, postSnowden cryptography has become a prominent research direction in recent years. In Eurocrypt 2015, Mironov and Stephens-Davidowitz proposed a novel concept named cryptographic reverse firewall (CRF) which can resist exfiltration of secret information from an arbitrarily compromised machine. In this work, we continue this line of research and present generic CRF constructions for several widely used cryptographic protocols based on a new notion named malleable smooth projective hash function. Our contributions can be summarized as follows. – We introduce the notion of malleable smooth projective hash function, which is an extension of the …
Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan
Cast2face: Assigning Character Names Onto Faces In Movie With Actor-Character Correspondence, Guangyu Gao, Mengdi Xu, Jialie Shen, Huangdong Ma, Shuicheng Yan
Research Collection School Of Computing and Information Systems
Automatically identifying characters in movies has attracted researchers' interest and led to several significant and interesting applications. However, due to the vast variation in character appearance as well as the weakness and ambiguity of available annotation, it is still a challenging problem. In this paper, we investigate this problem with the supervision of actor-character name correspondence provided by the movie cast. Our proposed framework, namely, Cast2Face, is featured by: 1) we restrict the assigned names within the set of character names in the cast; 2) for each character, by using the corresponding actor and movie name as keywords, we retrieve …
Processing Incomplete K Nearest Neighbor Search, Xiaoye Miao, Yunjun Gao, Gang Chen, Baihua Zheng, Huiyong Cui
Processing Incomplete K Nearest Neighbor Search, Xiaoye Miao, Yunjun Gao, Gang Chen, Baihua Zheng, Huiyong Cui
Research Collection School Of Computing and Information Systems
Given a setS of multidimensional objects and a query object q, a k nearest neighbor (kNN) query finds from S the k closest objects to q. This query is a fundamental problem in database, data mining, and information retrieval research. It plays an important role in a wide spectrum of real applications such as image recognition and location-based services. However, due to the failure of data transmission devices, improper storage, and accidental loss, incomplete data exist widely in those applications, where some dimensional values of data items are missing. In this paper, we systematically study incomplete k nearest neighbor (IkNN) …
Managing Egress Of Crowd During Infrastructure Disruption, Teck Hou Teng, Shih-Fen Cheng, Trong-Nghia Truong, Hoong Chuin Lau
Managing Egress Of Crowd During Infrastructure Disruption, Teck Hou Teng, Shih-Fen Cheng, Trong-Nghia Truong, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In a large indoor environment such as a sports arena or convention center, smooth egress of crowd after an event can be seriously affected if infrastructure such as elevators and escalators break down. In this paper, we propose a novel crowd simulator known as SIM-DISRUPT for simulating egress scenarios in non-emergency situations. To surface the impact of disrupted infrastructure on the egress of crowd, SIM-DISRUPT includes features that allow users to specify selective disruptions as well as strategies for controlling the distribution and egress choices of crowd. Using SIM-DISRUPT, we investigate effects of crowd distribution, egress choices and infrastructure disruptions …
A Privacy-Preserving Outsourced Functional Computation Framework Across Large-Scale Multiple Encrypted Domains, Ximeng Liu, Baodong Qin, Robert H. Deng, Rongxing Lu, Jianfeng Ma
A Privacy-Preserving Outsourced Functional Computation Framework Across Large-Scale Multiple Encrypted Domains, Ximeng Liu, Baodong Qin, Robert H. Deng, Rongxing Lu, Jianfeng Ma
Research Collection School Of Computing and Information Systems
In this paper, we propose a framework for privacy-preserving outsourced functional computation across large-scale multiple encrypted domains, which we refer to as POFD. With POFD, a user can obtain the output of a function computed over encrypted data from multiple domains while protecting the privacy of the function itself, its input and its output. Specifically, we introduce two notions of POFD, the basic POFD and its enhanced version, in order to tradeoff the levels of privacy protection and performance. We present three protocols, named Multi-domain Secure Multiplication protocol (MSM), Secure Exponent Calculation protocol with private Base (SECB), and Secure Exponent …
D-Watch: Embracing "Bad" Multipaths For Device-Free Localization With Cots Rfid Devices, Ju Wang, Jie Xiong, Hongbo Jiang, Xiaojiang Chen, Dingyi Fang
D-Watch: Embracing "Bad" Multipaths For Device-Free Localization With Cots Rfid Devices, Ju Wang, Jie Xiong, Hongbo Jiang, Xiaojiang Chen, Dingyi Fang
Research Collection School Of Computing and Information Systems
Device-free localization, which does not require any device attached to the target is playing a critical role in many applications such as intrusion detection, elderly monitoring, etc. This paper introduces D-Watch, a device-free system built on top of low cost commodity-off-the-shelf (COTS) RFID hardware. Unlike previous works which consider multipaths detrimental, D-Watch leverages the "bad" multipaths to provide a decimeter level localization accuracy without offline training. D-Watch harnesses the angle-of-arrival (AoA) information from the RFID tags' backscatter signals. The key intuition is that whenever a target blocks a signal's propagation path, the signal power experiences a drop which can be …
Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang
Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang
Research Collection School Of Computing and Information Systems
Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …
Ciphertext-Policy Attribute-Based Encryption With Partially Hidden Access Structure And Its Application To Privacy-Preserving Electronic Medical Record System In Cloud Environment, Lixian Liu, Junzuo Lai, Robert H. Deng, Yingjiu Li
Ciphertext-Policy Attribute-Based Encryption With Partially Hidden Access Structure And Its Application To Privacy-Preserving Electronic Medical Record System In Cloud Environment, Lixian Liu, Junzuo Lai, Robert H. Deng, Yingjiu Li
Research Collection School Of Computing and Information Systems
With the development of cloud computing, more and more sensitive data are uploaded to cloud by companies or individuals, which brings forth new challenges for outsourced data security and privacy. Ciphertext-policy attribute-based encryption (CP-ABE) provides fine-grained access control of encrypted data in the cloud; in a CP-ABE scheme, an access structure, also referred to as ciphertext-policy, is sent along with a ciphertext explicitly, and anyone who obtains a ciphertext can know the access structure associated with the ciphertext. In certain applications, access structures contain very sensitive information and must be protected from everyone except the users whose private key attributes …
Collective Personalized Change Classification With Multiobjective Search, Xin Xia, David Lo, Xinyu Wang, Xiaohu Yang
Collective Personalized Change Classification With Multiobjective Search, Xin Xia, David Lo, Xinyu Wang, Xiaohu Yang
Research Collection School Of Computing and Information Systems
Many change classification techniques have been proposed to identify defect-prone changes. These techniques consider all developers' historical change data to build a global prediction model. In practice, since developers have their own coding preferences and behavioral patterns, which causes different defect patterns, a separate change classification model for each developer can help to improve performance. Jiang, Tan, and Kim refer to this problem as personalized change classification, and they propose PCC+ to solve this problem. A software project has a number of developers; for a developer, building a prediction model not only based on his/her change data, but also on …
Semi-Automated Tool For Providing Effective Feedback On Programming Assignments, Min Yan Beh, Swapna Gottipati, David Lo, Venky Shankararaman
Semi-Automated Tool For Providing Effective Feedback On Programming Assignments, Min Yan Beh, Swapna Gottipati, David Lo, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Human grading of introductory programming assignments is tedious and error-prone, hence researchers have attempted to develop tools that support automatic assessment of programming code. However, most such efforts often focus only on scoring solutions, rather than assessing whether students correctly understand the problems. To aid the students improve programming skills, effective feedback on programming assignments plays an important role. Individual feedback generation is tedious and painstaking process. We present a tool that not only automatically generates the static and dynamic program analysis outcomes, but also clusters similar code submissions to provide scalable and effective feedback to the students. We studied …
Attacking Android Smartphone Systems Without Permissions, Mon Kywe Su, Yingjiu Li, Kunal Petal, Michael Grace
Attacking Android Smartphone Systems Without Permissions, Mon Kywe Su, Yingjiu Li, Kunal Petal, Michael Grace
Research Collection School Of Computing and Information Systems
Android requires third-party applications to request for permissions when they access critical mobile resources, such as users' personal information and system operations. In this paper, we present the attacks that can be launched without permissions. We first perform call graph analysis, component analysis and data-flow analysis on various parts of Android framework to retrieve unprotected APIs. Unprotected APIs provide a way of accessing resources without any permissions. We then exploit selected unprotected APIs and launch a number of attacks on Android phones. We discover that without requesting for any permissions, an attacker can access to device ID, phone service state, …
Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen
Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen
Research Collection School Of Computing and Information Systems
Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …
Lossy Key Encapsulation Mechanism And Its Applications, Yamin Liu, Xianhui Lu, Bao Li, Haiyang Xue
Lossy Key Encapsulation Mechanism And Its Applications, Yamin Liu, Xianhui Lu, Bao Li, Haiyang Xue
Research Collection School Of Computing and Information Systems
We introduce a new notion, lossy key encapsulation mechanism (lossy KEM), which enhances the notion of key encapsulation mechanism with lossiness, and can be more efficient than lossy trapdoor functions. We show that lossy KEM can be constructed from lossy trapdoor functions, lossy trapdoor relations, and entropic projective hashing. Using lossy KEM as a building block, several previous constructions of lossy encryption and deterministic public key encryption can be generalized and improved in efficiency.
Server-Aided Public Key Encryption With Keyword Search, Rongman Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xinyi Huang, Xiaofen Wang, Yongjun Wang
Server-Aided Public Key Encryption With Keyword Search, Rongman Chen, Yi Mu, Guomin Yang, Fuchun Guo, Xinyi Huang, Xiaofen Wang, Yongjun Wang
Research Collection School Of Computing and Information Systems
Public key encryption with keyword search (PEKS) is a well-known cryptographic primitive for secure searchable data encryption in cloud storage. Unfortunately, it is inherently subject to the (inside) offline keyword guessing attack (KGA), which is against the data privacy of users. Existing countermeasures for dealing with this security issue mainly suffer from low efficiency and are impractical for real applications. In this paper, we provide a practical and applicable treatment on this security vulnerability by formalizing a new PEKS system named server-aided public key encryption with keyword search (SA-PEKS). In SA-PEKS, to generate the keyword ciphertext/trapdoor, the user needs to …
Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang
Iterated Random Oracle: A Universal Approach For Finding Loss In Security Reduction, Fuchun Guo, Willy Susilo, Yi Mu, Rongmao Chen, Jianchang Lai, Guomin Yang
Research Collection School Of Computing and Information Systems
The indistinguishability security of a public-key cryptosystem can be reduced to a computational hard assumption in the random oracle model, where the solution to a computational hard problem is hidden in one of the adversary’s queries to the random oracle. Usually, there is a finding loss in finding the correct solution from the query set, especially when the decisional variant of the computational problem is also hard. The problem of finding loss must be addressed towards tight(er) reductions under this type. In EUROCRYPT 2008, Cash, Kiltz and Shoup proposed a novel approach using a trapdoor test that can solve the …
Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen
Validating Social Media Data For Automatic Persona Generation, Jisun An, Haewoon Kwak, Bernard J Jansen
Research Collection School Of Computing and Information Systems
Using personas during interactive design has considerable potential for product and content development. Unfortunately, personas have typically been a fairly static technique. In this research, we validate an approach for creating personas in real time, based on analysis of actual social media data in an effort to automate the generation of personas. We validate that social media data can be implemented as an approach for automating generating personas in real time using actual YouTube social media data from a global media corporation that produces online digital content. Using the organization's YouTube channel, we collect demographic data, customer interactions, and topical …
Towards Learning And Verifying Invariants Of Cyber-Physical Systems By Code Mutation, Yuqi Chen, Christopher M. Poskitt, Jun Sun
Towards Learning And Verifying Invariants Of Cyber-Physical Systems By Code Mutation, Yuqi Chen, Christopher M. Poskitt, Jun Sun
Research Collection School Of Computing and Information Systems
Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public infrastructure. In this short paper, we argue for the importance of constructing invariants (or models) of the physical behaviour exhibited by CPS, motivated by their applications to the control, monitoring, and attestation of components. To achieve this despite the inherent complexity of CPS, we propose a new technique for learning invariants that combines machine learning with ideas from mutation testing. …
Towards Learning And Verifying Invariants Of Cyber-Physical Systems By Code Mutation, Yuqi Chen, Christopher M. Poskitt, Jun Sun
Towards Learning And Verifying Invariants Of Cyber-Physical Systems By Code Mutation, Yuqi Chen, Christopher M. Poskitt, Jun Sun
Research Collection School Of Computing and Information Systems
Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public infrastructure. In this short paper, we argue for the importance of constructing invariants (or models) of the physical behaviour exhibited by CPS, motivated by their applications to the control, monitoring, and attestation of components. To achieve this despite the inherent complexity of CPS, we propose a new technique for learning invariants that combines machine learning with ideas from mutation testing. …
Towards Concolic Testing For Hybrid Systems, Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang
Towards Concolic Testing For Hybrid Systems, Pingfan Kong, Yi Li, Xiaohong Chen, Jun Sun, Meng Sun, Jingyi Wang
Research Collection School Of Computing and Information Systems
Hybrid systems exhibit both continuous and discrete behavior. Analyzing hybrid systems is known to be hard. Inspired by the idea of concolic testing (of programs), we investigate whether we can combine random sampling and symbolic execution in order to effectively verify hybrid systems. We identify a sufficient condition under which such a combination is more effective than random sampling. Furthermore, we analyze different strategies of combining random sampling and symbolic execution and propose an algorithm which allows us to dynamically switch between them so as to reduce the overall cost. Our method has been implemented as a web-based checker named …
Automated Verification Of Timed Security Protocols With Clock Drift, Li Li, Jun Sun
Automated Verification Of Timed Security Protocols With Clock Drift, Li Li, Jun Sun
Research Collection School Of Computing and Information Systems
Time is frequently used in security protocols to provide better security. For instance, critical credentials often have limited lifetime which improves the security against brute-force attacks. However, it is challenging to correctly use time in protocol design, due to the existence of clock drift in practice. In this work, we develop a systematic method to formally specify as well as automatically verify timed security protocols with clock drift. We first extend the previously proposed timed applied ππ -calculus as a formal specification language for timed protocols with clock drift. Then, we define its formal semantics based on timed logic rules, …
Improving Quality Of Use Case Documents Through Learning And User Interaction, Shuang Liu, Jun Sun, Hao Xiao, Bimlesh Wadhwa, Jin Song Dong, Xinyu Wang
Improving Quality Of Use Case Documents Through Learning And User Interaction, Shuang Liu, Jun Sun, Hao Xiao, Bimlesh Wadhwa, Jin Song Dong, Xinyu Wang
Research Collection School Of Computing and Information Systems
Use cases are widely used to capture user requirements based on interactions between different roles in the system. They are mostly documented in natural language and sometimes aided with graphical illustrations in the form of use case diagrams. Use cases serve as an important means to communicate among stakeholders, requirement engineers and system engineers as they are easy to understand and are produced early in the software development process. Having high quality use cases are beneficial in many ways, e.g., in avoiding inconsistency/incompleteness in requirements, in guiding system design, in generating test cases. In this work, we propose an approach …
Towards Using Concurrent Java Api Correctly, Shuang Liu, Guangdong Bai, Jun Sun, Jin Song Dong
Towards Using Concurrent Java Api Correctly, Shuang Liu, Guangdong Bai, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
Concurrent Programs are hard to analyze or debug due to the complex program logic and unpredictable execution environment. In practice, ordinary programmers often adopt existing well-designed concurrency related API (e.g., those in java.util.concurrent) so as to avoid dealing with these issues. These API can however often be used incorrectly, which results in hardto-debug concurrent bugs. In this work, we propose an approach for enforcing the correct usage of concurrency-related Java API. Our idea is to annotate concurrency-related Java classes with annotations related to misuse of these API and develop lightweight type checker to detect concurrent API misuse based on the …
Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata
Data Exfiltration Detection And Prevention: Virtually Distributed Pomdps For Practically Safer Networks, Sara Marie Mc Carthy, Arunesh Sinha, Milind Tambe, Pratyusa Manadhata
Research Collection School Of Computing and Information Systems
We address the challenge of detecting and addressing advanced persistent threats (APTs) in a computer network, focusing in particular on the challenge of detecting data exfiltration over Domain Name System (DNS) queries, where existing detection sensors are imperfect and lead to noisy observations about the network’s security state. Data exfiltration over DNS queries involves unauthorized transfer of sensitive data from an organization to a remote adversary through a DNS data tunnel to a malicious web domain. Given the noisy sensors, previous work has illustrated that standard approaches fail to satisfactorily rise to the challenge of detecting exfiltration attempts. Instead, we …
Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo
Hierarchical Visualization Of Video Search Results For Topic-Based Browsing, Yu-Gang Jiang, Jiajun Wang, Qiang Wang, Wei Liu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Existing video search engines return a ranked list of videos for each user query, which is not convenient for browsing the results of query topics that have multiple facets, such as the "early life," "personal life," and "presidency" of a query "Barack Obama." Organizing video search results into semantically structured hierarchies with nodes covering different topic facets can significantly improve the browsing efficiency for such queries. In this paper, we introduce a hierarchical visualization approach for video search result browsing, which can help users quickly understand the multiple facets of a query topic in a very well-organized manner. Given a …
Designing And Evaluating Business Process Models: An Experimental Approach, Yuecheng Martin Yu, Alexander Pelaez, Karl R. Lang
Designing And Evaluating Business Process Models: An Experimental Approach, Yuecheng Martin Yu, Alexander Pelaez, Karl R. Lang
Research Collection School Of Computing and Information Systems
This paper presents an experimental approach to compare the performance of alternative business process designs. We use an example case of an electronic group buying setting to demonstrate how our approach can be applied in practice. More specifically, we chose a standard business process, the sales process as implemented on a group buying platform, to illustrate how a business process may be redesigned in order to better meet the needs of customers. For that purpose, we introduce a social technology feature to support cooperation among buyers in the sales process and then analyze the performance impact of the proposed business …
A Decomposition Method For Estimating Recursive Logit Based Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
A Decomposition Method For Estimating Recursive Logit Based Route Choice Models, Tien Mai, Fabian Bastin, Emma Frejinger
Research Collection School Of Computing and Information Systems
Fosgerau et al. (2013) recently proposed the recursive logit (RL) model for route choice problems, that can be consistently estimated and easily used for prediction without any sampling of choice sets. Its estimation however requires solving many large-scale systems of linear equations, which can be computationally costly for real data sets. We design a decomposition (DeC) method in order to reduce the number of linear systems to be solved, opening the possibility to estimate more complex RL based models, for instance mixed RL models. We test the performance of the DeC method by estimating the RL model on two networks …