liu.seSearch for publications in DiVA
Change search
Link to record
Permanent link

Direct link
BETA
Carlsson, Niklas
Alternative names
Publications (10 of 80) Show all publications
Keskisärkkä, R., Li, H., Cheng, S., Carlsson, N. & Lambrix, P. (2019). An Ontology for Ice Hockey. In: ISWC 2019 Satellites: Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019). Paper presented at 18th International Semantic Web Conference (pp. 13-16).
Open this publication in new window or tab >>An Ontology for Ice Hockey
Show others...
2019 (English)In: ISWC 2019 Satellites: Proceedings of the ISWC 2019 Satellite Tracks (Posters & Demonstrations, Industry, and Outrageous Ideas) co-located with 18th International Semantic Web Conference (ISWC 2019), 2019, p. 13-16Conference paper, Published paper (Refereed)
Abstract [en]

Ice hockey is a highly popular sport that has seen significant increase in the use of sport analytics. To aid in such analytics, most major leagues collect and share increasing amounts of play-by-play data and other statistics. Additionally, some websites specialize in making such data available to the public in user-friendly forms. However, these sites fail to capture the semantic information of the data, and cannot be used to support more complex data requirements. In this paper, we present the design and development of an ice hockey ontology that provides improved knowledge representation, enables intelligent search and information acquisition, and helps when using information from multiple databases. Our ontology is substantially larger than previous ice hockey ontologies (that cover only a small part of the domain) and provides a formal and explicit representation of the ice hockey domain, supports information retrieval, data reuse, and complex performance metrics.

Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 456
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-160713 (URN)
Conference
18th International Semantic Web Conference
Available from: 2019-10-03 Created: 2019-10-03 Last updated: 2019-10-03
Sans Fuentes, C., Carlsson, N. & Lambrix, P. (2019). Player impact measures for scoring in ice hockey. In: Dimitris Karlis, Ioannis Ntzoufras, Sotiris Drikos (Ed.), Proceedings of MathSport International 2019 Conference: . Paper presented at MathSport International Conference, Athens, 1-3 July 2019 (pp. 307-317). Athen: Athens University of Economics and Business
Open this publication in new window or tab >>Player impact measures for scoring in ice hockey
2019 (English)In: Proceedings of MathSport International 2019 Conference / [ed] Dimitris Karlis, Ioannis Ntzoufras, Sotiris Drikos, Athen: Athens University of Economics and Business , 2019, p. 307-317Conference paper, Published paper (Refereed)
Abstract [en]

A commonly used method to evaluate player performance is to attribute values to the different actions that players perform and sum up these values every time a player performs these actions. In ice hockey, such metrics include the number of goals, assists, points, plus-minus statistics and recently Corsi and Fenwick. However, these metrics do not capture the context of player actions and the impact they have on the outcome of later actions. Therefore, recent works have introduced more advanced metrics that take into account the context of the actions and perform look-ahead. The use of look-ahead is particularly valuable in low-scoring sports such as ice hockey. In this paper, we first extend a recent approach based on reinforcement learning for measuring a player's impact on a team's scoring. Second, using NHL play-by-play data for several regular seasons, we analyze and compare these and other traditional measures of player impact. Third, we introduce notions of streaks and show that these may provide information about good players, but do not provide a good predictor for the impact that a player will have the next game. Finally, streaks are compared for different player categories, highlighting differences between player positions and correlations with player salaries.

Place, publisher, year, edition, pages
Athen: Athens University of Economics and Business, 2019
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-157992 (URN)
Conference
MathSport International Conference, Athens, 1-3 July 2019
Available from: 2019-06-22 Created: 2019-06-22 Last updated: 2019-06-26Bibliographically approved
Nsolo, E., Lambrix, P. & Carlsson, N. (2019). Player Valuation in European Football. In: Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann (Ed.), Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics: co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018). Paper presented at 5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings (pp. 42-54). Cham: Springer, 11330
Open this publication in new window or tab >>Player Valuation in European Football
2019 (English)In: Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics: co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018) / [ed] Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann, Cham: Springer, 2019, Vol. 11330, p. 42-54Conference paper, Published paper (Refereed)
Abstract [en]

As the success of a team depends on the performance of individual players, the valuation of player performance has become an important research topic. In this paper, we compare and contrast which attributes and skills best predict the success of individual players in their positions in five European top football leagues. Further, we evaluate different machine learning algorithms regarding prediction performance. Our results highlight features distinguishing top-tier players and show that prediction performance is higher for forwards than for other positions, suggesting that equally good prediction of defensive players may require more advanced metrics.

Place, publisher, year, edition, pages
Cham: Springer, 2019
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11330
Keywords
Sports analytics, football, soccer
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-153594 (URN)10.1007/978-3-030-17274-9_4 (DOI)9783030172732 (ISBN)9783030172749 (ISBN)
Conference
5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings
Available from: 2018-12-22 Created: 2018-12-22 Last updated: 2019-06-25Bibliographically approved
Ljung, D., Carlsson, N. & Lambrix, P. (2018). Player Pairs Valuation in Ice Hockey. In: Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann (Ed.), Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics: co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018). Paper presented at 5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018 (pp. 82-92). Cham: Springer, 11330
Open this publication in new window or tab >>Player Pairs Valuation in Ice Hockey
2018 (English)In: Proceedings of the 5th Workshop on Machine Learning and Data Mining for Sports Analytics: co-located with 2018 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2018) / [ed] Ulf Brefeld, Jesse Davis, Jan Van Haaren, Albrecht Zimmermann, Cham: Springer, 2018, Vol. 11330, p. 82-92Conference paper, Published paper (Refereed)
Abstract [en]

To overcome the shortcomings of simple metrics for evaluating player performance, recent works have introduced more advanced metrics that take into account the context of the players’ actions and perform look-ahead. However, as ice hockey is a team sport, knowing about individual ratings is not enough and coaches want to identify players that play particularly well together. In this paper we therefore extend earlier work for evaluating the performance of players to the related problem of evaluating the performance of player pairs. We experiment with data from seven NHL seasons, discuss the top pairs, and present analyses and insights based on both the absolute and relative ice time together.

Place, publisher, year, edition, pages
Cham: Springer, 2018
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 11330Lecture notes in artificial intelligence ; 11330
Keywords
Sports analytics, ice hockey
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-153593 (URN)10.1007/978-3-030-17274-9_7 (DOI)9783030172732 (ISBN)9783030172749 (ISBN)
Conference
5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018
Available from: 2018-12-22 Created: 2018-12-22 Last updated: 2019-06-25Bibliographically approved
de Leng, D., Tiger, M., Almquist, M., Almquist, V. & Carlsson, N. (2018). Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs. In: Proceedings of the 2nd Network Traffic Measurement and Analysis Conference (TMA): . Paper presented at Network Traffic Measurement and Analysis Conference, Vienna, Austria, 26-29 June, 2018 (pp. 1-8).
Open this publication in new window or tab >>Second Screen Journey to the Cup: Twitter Dynamics during the Stanley Cup Playoffs
Show others...
2018 (English)In: Proceedings of the 2nd Network Traffic Measurement and Analysis Conference (TMA), 2018, p. 1-8Conference paper, Oral presentation only (Refereed)
Abstract [en]

With Twitter and other microblogging services, users can easily express their opinion and ideas in short text messages. A recent trend is that users use the real-time property of these services to share their opinions and thoughts as events unfold on TV or in the real world. In the context of TV broadcasts, Twitter (over a mobile device, for example) is referred to as a second screen. This paper presents the first characterization of the second screen usage over the playoffs of a major sports league. We present both temporal and spatial analysis of the Twitter usage during the end of the National Hockey League (NHL) regular season and the 2015 Stanley Cup playoffs. Our analysis provides insights into the usage patterns over the full 72-day period and with regards to in-game events such as goals, but also with regards to geographic biases. Quantifying these biases and the significance of specific events, we then discuss and provide insights into how the playoff dynamics may impact advertisers and third-party developers that try to provide increased personalization.

Keywords
Second Screen, Social Media, Twitter, National Hockey League, Personalization
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-148431 (URN)10.23919/TMA.2018.8506531 (DOI)000454696100018 ()978-3-903176-09-6 (ISBN)978-1-5386-7152-8 (ISBN)
Conference
Network Traffic Measurement and Analysis Conference, Vienna, Austria, 26-29 June, 2018
Funder
CUGS (National Graduate School in Computer Science)Swedish Research Council
Note

Funding agencies:  Swedish Research Council (VR); National Graduate School in Computer Science, Sweden (CUGS) Swedish Research Council (VR); National Graduate School in Computer Science, Sweden (CUGS)

Available from: 2018-06-11 Created: 2018-06-11 Last updated: 2019-01-21
Nykvist, C., Sjöström, L., Gustafsson, J. & Carlsson, N. (2018). Server-Side Adoption of Certificate Transparency. In: Robert Beverly, Georgios Smaragdakis, Anja Feldmann (Ed.), Passive and Active Measurement: 19th International Conference, PAM 2018, Berlin, Germany, March 26–27, 2018, Proceedings. Paper presented at Tha 19th International Conference, PAM 2018, Berlin, Germany, March 26–27, 2018 (pp. 186-199). Cham: Springer, 10771
Open this publication in new window or tab >>Server-Side Adoption of Certificate Transparency
2018 (English)In: Passive and Active Measurement: 19th International Conference, PAM 2018, Berlin, Germany, March 26–27, 2018, Proceedings / [ed] Robert Beverly, Georgios Smaragdakis, Anja Feldmann, Cham: Springer, 2018, Vol. 10771, p. 186-199Conference paper, Published paper (Refereed)
Abstract [en]

Certificate Transparency (CT) was developed to mitigate shortcomings in the TLS/SSL landscape and to assess the trustworthiness of Certificate Authorities (CAs) and the certificates they create. With CT, certificates should be logged in public, audible, append-only CT logs and servers should provide clients (browsers) evidence, in the form of Signed Certificate Timestamps (SCTs), that the certificates that they present have been logged in credible CT logs. These SCTs can be delivered using three different methods: (i) X.509v3 extension, (ii) TLS extension, and (iii) OSCP stapling. In this paper, we develop a client-side measurement tool that implements all three methods and use the tool to analyze the SCT adoption among the one-million most popular web domains. Using two snapshots (from May and Oct. 2017), we answer a wide range of questions related to the delivery choices made by different domains, identify differences in the certificates used by these domains, the CT logs they use, and characterize the overheads and potential performance impact of the SCT delivery methods. By highlighting some of the tradeoffs between the methods and differences in the websites selecting them, we provide insights into the current SCT adoption status and differences in how domains have gone upon adopting this new technology.

Place, publisher, year, edition, pages
Cham: Springer, 2018
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10771
National Category
Computer Sciences Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-156664 (URN)10.1007/978-3-319-76481-8_14 (DOI)2-s2.0-85043581742 (Scopus ID)9783319764801 (ISBN)9783319764818 (ISBN)
Conference
Tha 19th International Conference, PAM 2018, Berlin, Germany, March 26–27, 2018
Available from: 2019-05-06 Created: 2019-05-06 Last updated: 2019-05-13Bibliographically approved
Vapen, A., Carlsson, N., Mahanti, A. & Shahmehri, N. (2016). A Look at the Third-Party Identity Management Landscape. IEEE Internet Computing, 20(2), 18-25
Open this publication in new window or tab >>A Look at the Third-Party Identity Management Landscape
2016 (English)In: IEEE Internet Computing, ISSN 1089-7801, E-ISSN 1941-0131, Vol. 20, no 2, p. 18-25Article in journal (Refereed) Published
Abstract [en]

Many websites act as relying parties (RPs) by allowing access to their services via third-party identity providers (IDPs), such as Facebook and Google. Using IDPs simplifies account creation, login activity, and information sharing across websites. However, different websites use of IDPs can have significant security and privacy implications for users. Here, the authors provide an overview of third-party identity managements current landscape. Using datasets collected through manual identification and large-scale crawling, they answer questions related to which sites act as RPs, which sites are the most successful IDPs, and how different classes of RPs select their IDPs.

Place, publisher, year, edition, pages
IEEE COMPUTER SOC, 2016
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-127053 (URN)10.1109/MIC.2016.38 (DOI)000372015500003 ()
Available from: 2016-04-13 Created: 2016-04-13 Last updated: 2018-01-10
Hiran, R., Carlsson, N. & Shahmehri, N. (2016). Does Scale, Size, and Locality Matter?: Evaluation of Collaborative BGP Security Mechanisms. In: 2016 IFIP NETWORKING CONFERENCE (IFIP NETWORKING) AND WORKSHOPS: . Paper presented at IFIP Networking Conference (IFIP Networking) and Workshops, Vienna, Austria, May 2016 (pp. 261-269). IEEE
Open this publication in new window or tab >>Does Scale, Size, and Locality Matter?: Evaluation of Collaborative BGP Security Mechanisms
2016 (English)In: 2016 IFIP NETWORKING CONFERENCE (IFIP NETWORKING) AND WORKSHOPS, IEEE , 2016, p. 261-269Conference paper, Published paper (Refereed)
Abstract [en]

The Border Gateway Protocol (BGP) was not designed with security in mind and is vulnerable to many attacks, including prefix/subprefix hijacks, interception attacks, and imposture attacks. Despite many protocols having been proposed to detect or prevent such attacks, no solution has been widely deployed. Yet, the effectiveness of most proposals relies on largescale adoption and cooperation between many large Autonomous Systems (AS). In this paper we use measurement data to evaluate some promising, previously proposed techniques in cases where they are implemented by different subsets of ASes, and answer questions regarding which ASes need to collaborate, the importance of the locality and size of the participating ASes, and how many ASes are needed to achieve good efficiency when different subsets of ASes collaborate. For our evaluation we use topologies and routing information derived from real measurement data. We consider collaborative detection and prevention techniques that use (i) prefix origin information, (ii) route path updates, or (iii) passively collected round-trip time (RTT) information. Our results and answers to the above questions help determine the effectiveness of potential incremental rollouts, incentivized or required by regional legislation, for example. While there are differences between the techniques and two of the three classes see the biggest benefits when detection/prevention is performed close to the source of an attack, the results show that significant gains can be achieved even with only regional collaboration.

Place, publisher, year, edition, pages
IEEE, 2016
National Category
Computer Sciences Communication Systems
Identifiers
urn:nbn:se:liu:diva-129430 (URN)10.1109/IFIPNetworking.2016.7497237 (DOI)000383224900030 ()978-3-9018-8283-8 (ISBN)
Conference
IFIP Networking Conference (IFIP Networking) and Workshops, Vienna, Austria, May 2016
Available from: 2016-06-19 Created: 2016-06-19 Last updated: 2018-01-10
Vapen, A., Carlsson, N. & Shahmehri, N. (2016). Longitudinal Analysis of the Third-party Authentication Landscape. In: : . Paper presented at NDSS Workshop on Understanding and Enhancing Online Privacy Workshop (UEOP@NDSS).21-24 February 2016 Catamaran Resort Hotel & Spa in San Diego, California. Internet Society
Open this publication in new window or tab >>Longitudinal Analysis of the Third-party Authentication Landscape
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Many modern websites offer single sign-on (SSO) services, which allow the user to use an existing account with a third-party website such as Facebook to authenticate. When using SSO the user must approve an app-rights agreement that specifies what data related to the user can be shared between the two websites and any actions (e.g., posting comments) that the origin website is allowed to perform on behalf of the user on the third-party provider (e.g., Facebook). Both cross-site data sharing and actions performed on behalf of the user can have significant privacy implications. In this paper we present a longitudinal study of the third-party authentication landscape, its structure, and the protocol usage, data sharing, and actions associated with individual third-party relationships. The study captures the current state, changes in the structure, protocol usage, and information leakage risks.

Place, publisher, year, edition, pages
Internet Society, 2016
National Category
Computer Systems
Identifiers
urn:nbn:se:liu:diva-127301 (URN)1-891562-44-4 (ISBN)
Conference
NDSS Workshop on Understanding and Enhancing Online Privacy Workshop (UEOP@NDSS).21-24 February 2016 Catamaran Resort Hotel & Spa in San Diego, California
Note

DOI does not work: 10.14722/ueop.2016.23008

Available from: 2016-04-19 Created: 2016-04-19 Last updated: 2018-09-20Bibliographically approved
Linder, T., Persson, P., Forsberg, A., Danielsson, J. & Carlsson, N. (2016). On Using Crowd-sourced Network Measurements for Performance Prediction. In: Proc. IEEE/IFIP Wireless On-demand Network Systems and Services Conference (IEEE/IFIP WONS), Cortina d'Ampezzo, Italy, Jan. 2016.: . Paper presented at Proc. IEEE/IFIP Wireless On-demand Network Systems and Services Conference (IEEE/IFIP WONS), Cortina d'Ampezzo, Italy, Jan. 2016. (pp. 1-8). IEEE Computer Society Digital Library
Open this publication in new window or tab >>On Using Crowd-sourced Network Measurements for Performance Prediction
Show others...
2016 (English)In: Proc. IEEE/IFIP Wireless On-demand Network Systems and Services Conference (IEEE/IFIP WONS), Cortina d'Ampezzo, Italy, Jan. 2016., IEEE Computer Society Digital Library, 2016, p. 1-8Conference paper, Published paper (Refereed)
Abstract [en]

Geo-location-based bandwidth prediction together with careful download scheduling for mobile clients can be used to minimize download times, reduce energy usage, and improve streaming performance. Although crowd-sourced measurements provide an important prediction tool, little is known about the prediction accuracy and improvements such datasets can provide. In this paper we use a large-scale crowd-sourced dataset from Bredbandskollen, Sweden's primary speedtest service, to evaluate the prediction accuracy and achievable performance improvements with such data. We first present a scalable performance map methodology that allows fast insertion/retrieval of geo-sparse measurements, and use this methodology to characterize the Bredbandskollen usage. Second, we analyze the bandwidth variations and predictability of the download speeds observed within and across different locations, when accounting for various factors. Third, we evaluate the relative performance improvements achievable by users leveraging different subsets of measurements (capturing effects of limited sharing or filtering based on operator, network technology, or both) when predicting opportune locations to perform downloads. Our results are encouraging for both centralized and peer-to-peer performance map solutions. For example, most measurements are done in locations with many measurements and good prediction accuracy, and further improvements are possible through filtering (e.g., based on operator and technology) or limited information sharing.

Place, publisher, year, edition, pages
IEEE Computer Society Digital Library, 2016
National Category
Computer Sciences Communication Systems
Identifiers
urn:nbn:se:liu:diva-129427 (URN)000377341500005 ()978-3-901882-79-1 (ISBN)
Conference
Proc. IEEE/IFIP Wireless On-demand Network Systems and Services Conference (IEEE/IFIP WONS), Cortina d'Ampezzo, Italy, Jan. 2016.
Available from: 2016-06-19 Created: 2016-06-19 Last updated: 2018-03-26
Organisations

Search in DiVA

Show all publications