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Jason M. Morawski

Bio: Jason M. Morawski is an academic researcher from University of Alberta. The author has contributed to research in topics: Collaborative filtering & Recommender system. The author has an hindex of 2, co-authored 2 publications receiving 54 citations.

Papers
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Journal ArticleDOI
TL;DR: A novel approach to incorporate spatial, temporal, and social context into a traditional collaborative filtering algorithm is introduced, and it is demonstrated that this approach is at the least competitive with existing state-of-the-art location recommenders.
Abstract: Location-based social networks (LBSNs) such as Foursquare, Brightkite, and Gowalla are a growing area where recommendation algorithms find a practical application. With an ever-increasing variety of venues to choose from deciding on a destination can be overwhelming. Recommenders aid their users in the decision-making process by providing a list of locations likely to be relevant to the user’s needs and interests. Traditional collaborative filtering algorithms consider relationships between users and locations, finding users to be similar only if their location histories overlap. However, the availability of spatial, temporal, and social information in an LBSN offers an opportunity to improve the quality of a recommendation engine. Social network data allows us to connect users who can directly influence each other’s decisions. Temporal data allows us to account for the drifting preferences of users, giving more weight to recent location visits over historical selections, and taking advantages of repetitive behaviors. Spatial information allows us to focus recommendations on locations close to the user, keeping our recommendations relevant as a user travels. We introduce a novel approach to incorporate spatial, temporal, and social context into a traditional collaborative filtering algorithm. We evaluate our method on data sets collected from three LBSNs, and demonstrate that our approach is at the least competitive with existing state-of-the-art location recommenders.

48 citations

Journal ArticleDOI
TL;DR: This work proposes a hybridization of collaborative filtering with a content filter using a fuzzy taste vector that is at least as accurate as existing fuzzy recommenders and is particularly effective on sparse data sets.
Abstract: Recommendation engines are one of the “discovery” products built into integrated library systems. These are a subclass of enterprise systems designed specifically for public and research libraries that incorporate an electronic card catalogue, circulation and inventory management, personnel and payroll systems, etc. The system vendors offer customizations for different contexts of specific library systems, but cannot create a bespoke solution for every customer. Our partner, an Edmonton-area company, is filling this gap for a consortium of rural libraries in Alberta by creating a mobile app that interfaces with their electronic card catalog. Rural libraries are generally smaller than major urban public libraries, meaning that their holdings are limited overall, and within any given genre. This poses a severe problem for traditional collaborative-filtering recommender algorithms, as the item sets for recommendations are limited by supply rather than by readers’ interests. The library's relatively small clientele also limits the item sets available for comparison. To deal with this ongoing “cold-start” problem, we propose a hybridization of collaborative filtering with a content filter using a fuzzy taste vector. Experiments on two benchmark recommender data sets show that this approach is at least as accurate as existing fuzzy recommenders and is particularly effective on sparse data sets.

21 citations


Cited by
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Book
01 Jan 2016
TL;DR: It’s time to dust off the gloves and get ready for the cold weather.
Abstract: 1 インフラを構築する(AWSにおけるインフラ;VPCを構成する;VPCとオンプレミス環境とを接続する) 2 ファイルオブジェクトを保存・共有・公開する(オブジェクトストレージS3の機能;ファイルストレージとして利用する;Webサーバーを構築する;信頼性とコストのバランスをとりたい) 3 アプリケーションサーバーを構築する(Amazon EC2とAWS Lambda;スケーラビリティーを高める;サーバーレスでプログラムを動かす;データベースサービスを活用する) 4 AWSシステムを管理する(リソース監視と異常検知・通報;耐障害性を高める仕組みとバックアップ&リカバリー;構成管理)

350 citations

Patent
15 Jan 2015
TL;DR: In this paper, the authors described improved capabilities for a computer program product embodied in a computer readable medium that, when executing on one or more computers, helps determine an unknown user's preferences through the use of internet based social interactive graphical representations on a computer facility by performing the steps of ascertaining preferences of a plurality of users who are part of an internet-based social interactive construct.
Abstract: In embodiments of the present invention improved capabilities are described for a computer program product embodied in a computer readable medium that, when executing on one or more computers, helps determine an unknown user's preferences through the use of internet based social interactive graphical representations on a computer facility by performing the steps of (1) ascertaining preferences of a plurality of users who are part of an internet based social interactive construct, wherein the plurality of users become a plurality of known users; (2) determining the internet based social interactive graphical representation for the plurality of known users; and (3) inferring the preferences of an unknown user present in the internet based social interactive graphical representation of the plurality of known users based on the interrelationships between the unknown user and the plurality of known users within the graphical representation.

215 citations

Journal ArticleDOI
TL;DR: This article strives to present a systematic introduction of DAO, including its concept and characteristics, research framework, typical implementations, challenges, and future trends, including a novel reference model for DAO which employs a five-layer architecture.
Abstract: Decentralized autonomy is a long-standing research topic in information sciences and social sciences. The self-organization phenomenon in natural ecosystems, the Cyber Movement Organizations (CMOs) on the Internet, and the Distributed Artificial Intelligence (DAI), and so on, can all be regarded as its early manifestations. In recent years, the rapid development of blockchain technology has spawned the emergence of the so-called Decentralized Autonomous Organization [DAO, sometimes labeled as Decentralized Autonomous Corporation (DAC)], which is a new organization form that the management and operational rules are typically encoded on blockchain in the form of smart contracts, and can autonomously operate without centralized control or third-party intervention. DAO is expected to overturn the traditional hierarchical management model and significantly reduce organizations’ costs on communication, management, and collaboration. However, DAO still faces many challenges, such as security and privacy issue, unclear legal status, and so on. In this article, we strive to present a systematic introduction of DAO, including its concept and characteristics, research framework, typical implementations, challenges, and future trends. Especially, a novel reference model for DAO which employs a five-layer architecture is proposed. This article is aimed at providing helpful guidance and reference for future research efforts.

136 citations

Book ChapterDOI
01 Jan 2018
TL;DR: This chapter delves into the cognitive radio (CR) and its social relations and makes sufficient exploits in establishing a scheme that will be based on social-based cooperative sensing scheme (SBC).
Abstract: The mobile networks seem to have a steady future in the direction of the recent emergence of socially aware cognitive mobile networks. Their style and design are specifically made in improving shared spectrum space access, in cooperative spectrum sensing, and in enhancing device-to-device communications. Socially aware mobile networks do have enough potential to amass sufficient returns in the efficacy of the spectrum and also to march and gain a considerable amount of increase in the capacity of the network. Even though there are lot of gains in its potency to be reaped yet, still there seems to be enough challenges that are both businessand technical-related that have to be taken care of. This chapter delves into the cognitive radio (CR) and its social relations and also makes sufficient exploits in establishing a scheme that will be based on social-based cooperative sensing scheme (SBC).

85 citations

Journal ArticleDOI
TL;DR: This paper presents the first timely and comprehensive reference for energy-efficiency recommendation systems and provides an original taxonomy of these systems based on specified criteria, including the nature of the recommender engine, its objective, computing platforms, evaluation metrics and incentive measures.

62 citations