%0 Conference Paper %1 limesWebUI %A Sherif, Mohamed Ahmed %A Pestryakova, Svetlana %A Dreßler, Kevin %A Ngomo, Axel-Cyrille Ngonga %B 18th International Semantic Web Conference (ISWC 2019) %D 2019 %I CEUR-WS.org %K 2019 Svetlana dice group_aksw kevin limbo limes ngonga opal sage sherif simba slipo %T LimesWebUI – Link Discovery Made Simple %U http://svn.aksw.org/papers/2019/ISWC_limesWebUI/public.pdf %X In this paper we present LimesWebUI, our web interface of Limes. Limes, the Link Discovery Framework for Metric Spaces, is a framework for dis- covering links between entities contained in Linked Data sources. LimesWebUI assists the end user during the link discovery process. By representing the link specifications (LS) as interlocking blocks, our interface eases the manual creation of links for users who already know which LS they would like to execute. How- ever, most users do not know which LS suits their linking task best and therefore need help throughout this process. Hence, our interface provides wizards which allow the easy configuration of many link discovery machine learning algorithms, that does not require the user to enter a manual LS. We evaluate the usability of the interface by using the standard system usability scale questionnaire. Our over- all usability score of 76.5 suggests that the online interface is consistent, easy to use, and the various functions of the system are well integrated.

@inproceedings{limesWebUI, abstract = {In this paper we present LimesWebUI, our web interface of Limes. Limes, the Link Discovery Framework for Metric Spaces, is a framework for dis- covering links between entities contained in Linked Data sources. LimesWebUI assists the end user during the link discovery process. By representing the link specifications (LS) as interlocking blocks, our interface eases the manual creation of links for users who already know which LS they would like to execute. How- ever, most users do not know which LS suits their linking task best and therefore need help throughout this process. Hence, our interface provides wizards which allow the easy configuration of many link discovery machine learning algorithms, that does not require the user to enter a manual LS. We evaluate the usability of the interface by using the standard system usability scale questionnaire. Our over- all usability score of 76.5 suggests that the online interface is consistent, easy to use, and the various functions of the system are well integrated.}, added-at = {2024-03-04T14:13:35.000+0100}, author = {Sherif, Mohamed Ahmed and Pestryakova, Svetlana and Dre{\ss}ler, Kevin and Ngomo, Axel-Cyrille Ngonga}, bdsk-url-1 = {http://svn.aksw.org/papers/2019/ISWC_limesWebUI/public.pdf}, biburl = {https://www.bibsonomy.org/bibtex/28bfa8720576ec8970d0185b2408653b6/aksw}, booktitle = {18th International Semantic Web Conference (ISWC 2019)}, interhash = {2276f42d81c6ce4d1b4e49b506efc5a4}, intrahash = {8bfa8720576ec8970d0185b2408653b6}, keywords = {2019 Svetlana dice group_aksw kevin limbo limes ngonga opal sage sherif simba slipo}, publisher = {CEUR-WS.org}, timestamp = {2024-03-04T14:13:35.000+0100}, title = {{LimesWebUI – Link Discovery Made Simple}}, url = {http://svn.aksw.org/papers/2019/ISWC_limesWebUI/public.pdf}, year = 2019 }