@inproceedings{SchwarzerBSM17,
	title = {Citolytics: {A} {Link}-based {Recommender} {System} for {Wikipedia}},
	isbn = {978-1-4503-4652-8},
	shorttitle = {Citolytics},
	url = {paper=https://www.gipp.com/wp-content/papercite-data/pdf/schwarzer2017.pdf code=https://github.com/wikimedia/citolytics},
	doi = {10.1145/3109859.3109981},
	abstract = {We present Citolytics - a novel link-based recommendation system for Wikipedia articles. In a preliminary study, Citolytics achieved promising results compared to the widely used text-based approach of Apache Lucene's MoreLikeThis (MLT). In this demo paper, we describe how we plan to integrate Citolytics into the Wikipedia infrastructure by using Elasticsearch and Apache Flink to serve recommendations for Wikipedia articles. Additionally, we propose a large-scale online evaluation design using the Wikipedia Android app. Working with Wikipedia data has several unique advantages. First, the availability of a very large user sample contributes to statistically significant results. Second, the openness of Wikipedia's architecture allows making our source code and evaluation data public, thus benefiting other researchers. If link-based recommendations show promise in our online evaluation, a deployment of the presented system within Wikipedia would have a far-reaching impact on Wikipedia's more than 30 million users.},
	booktitle = {Proceedings of the 11th {ACM} {Conference} on {Recommender} {Systems} ({RecSys})},
	publisher = {ACM},
	author = {Schwarzer, Malte and Breitinger, Corinna and Schubotz, Moritz and Meuschke, Norman and Gipp, Bela},
	month = aug,
	year = {2017},
	note = {Venue Rating: CORE B},
	keywords = {Literature Recommendation},
	pages = {360--361},
}

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