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Title | Preflib |
Description | PrefLib : A Library for Preferences Menu ▾ ❖ Format ❖ Datasets ❖ Search PrefLib PrefLib is a reference library of preference data maintained by Nicholas M |
Keywords | N/A |
WebSite | preflib.org |
Host IP | 173.236.165.7 |
Location | United States |
Site | Rank |
US$271,873
Last updated: 2023-05-14 09:50:36
preflib.org has Semrush global rank of 38,931,123. preflib.org has an estimated worth of US$ 271,873, based on its estimated Ads revenue. preflib.org receives approximately 31,370 unique visitors each day. Its web server is located in United States, with IP address 173.236.165.7. According to SiteAdvisor, preflib.org is safe to visit. |
Purchase/Sale Value | US$271,873 |
Daily Ads Revenue | US$251 |
Monthly Ads Revenue | US$7,529 |
Yearly Ads Revenue | US$90,346 |
Daily Unique Visitors | 2,092 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
preflib.org. | A | 299 | IP: 173.236.165.7 |
preflib.org. | NS | 14400 | NS Record: ns3.dreamhost.com. |
preflib.org. | NS | 14400 | NS Record: ns2.dreamhost.com. |
preflib.org. | NS | 14400 | NS Record: ns1.dreamhost.com. |
PrefLib : A Library for Preferences Menu ▾ ❖ Format ❖ Datasets ❖ Search PrefLib PrefLib is a reference library of preference data maintained by Nicholas Mattei and Simon Rey . The original version of this website was developed by Nicholas Mattei and Toby Walsh . We aim at providing a comprehensive resource for the multiple research communities that deal with preferences: computational social choice, recommender systems, data mining, machine learning, combinatorial optimization, to name just a few. The strength of PrefLib is to provide carefully curated data, formatted in a unified format. We encourage the users to read the detailed explanations that we provide regarding the format and the modelisation choices. Once everything is clear, feel free to explore the datasets we are hosting, or to search for specific files that may interest you. PrefLib-Tools Providing data is only the first step, the next one being actually using the data. To help you with that, we provide a Python library |
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Domain Name: PREFLIB.ORG Registry Domain ID: D168096123-LROR Registrar WHOIS Server: whois.dreamhost.com Registrar URL: http://www.dreamhost.com/ Updated Date: 2020-03-05T01:42:32Z Creation Date: 2013-03-08T04:57:27Z Registry Expiry Date: 2022-03-08T04:57:27Z Registrar: DreamHost LLC Registrar IANA ID: 431 Registrar Abuse Contact Email: abuse@dreamhost.com Registrar Abuse Contact Phone: +213.2719359 Domain Status: ok https://icann.org/epp#ok Registrant Organization: Nicholas Mattei Registrant State/Province: KY Registrant Country: US Name Server: NS1.DREAMHOST.COM Name Server: NS2.DREAMHOST.COM Name Server: NS3.DREAMHOST.COM DNSSEC: unsigned URL of the ICANN Whois Inaccuracy Complaint Form https://www.icann.org/wicf/) >>> Last update of WHOIS database: 2021-12-26T14:04:24Z <<< |