[ACM Press the 5th Information Interaction in Context Symposium - Regensburg, Germany (2014.08.26-2014.08.30)] Proceedings of the 5th Information Interaction in Context Symposium on - IIiX '14 - Contextual modeling content-based approaches for new-item recommendation

[ACM Press the 5th Information Interacti

✍ Codina, Victor; Oliva, Luis 📂 Article 📅 2014 🏛 ACM Press ⚖ 294 KB

[ACM Press the 5th Information Interacti

[ACM Press the 5th Information Interaction in Context Symposium - Regensburg, Germany (2014.08.26-2014.08.30)] Proceedings of the 5th Information Interaction in Context Symposium on - IIiX '14 - Interactive summarization of social media

✍ Li, Wen; Eickhoff, Carsten; de Vries, Arjen P. 📂 Article 📅 2014 🏛 ACM Press ⚖ 657 KB

[ACM Press the 5th Information Interacti

[ACM Press the 5th Information Interaction in Context Symposium - Regensburg, Germany (2014.08.26-2014.08.30)] Proceedings of the 5th Information Interaction in Context Symposium on - IIiX '14 - Characterizing relevance with eye-tracking measures

✍ Gwizdka, Jacek 📂 Article 📅 2014 🏛 ACM Press ⚖ 932 KB

[ACM Press the second international symp

[ACM Press the second international symposium - London, United Kingdom (2008.10.14-2008.10.17)] Proceedings of the second international symposium on Information interaction in context - IIiX '08 - Learning user interests for a session-based personalized search

✍ Daoud, Mariam; Tamine-Lechani, Lynda; Boughanem, Mohand 📂 Article 📅 2008 🏛 ACM Press ⚖ 688 KB

[ACM Press the second international symp

[ACM Press the second international symposium - London, United Kingdom (2008.10.14-2008.10.17)] Proceedings of the second international symposium on Information interaction in context - IIiX '08 - Learning user interests for a session-based personalized search

✍ Daoud, Mariam; Tamine-Lechani, Lynda; Boughanem, Mohand 📂 Article 📅 2008 🏛 ACM Press ⚖ 688 KB

It is now widely assumed in personalized information retrieval (IR) area that user interests can provide substantial clues for document relevance estimation. User interests reflect generally the user background and topics of interests. However most of the proposed personalized retrieval models and s