Diversity and novelty in information retrieval

Download

index.pdf

Date

2013-09-02

Author

Santos, Rodrygo L.T.
Castells, Pablo
Altıngövde, İsmail Sengör
Can, Fazli

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

151
views

87
downloads

This tutorial aims to provide a unifying account of current research on diversity and novelty in different IR domains, namely, in the context of search engines, recommender systems, and data streams.

Subject Keywords

Relevance, Diversity, Novelty, Ambiguity, Redundancy

URI

https://hdl.handle.net/11511/46230

DOI

https://doi.org/10.1145/2484028.2484187

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Diversity and Novelty in Web Search, Recommender Systems and Data Streams Santos, Rodrygo L. T.; Castells, Pablo; Altıngövde, İsmail Sengör; Can, Fazli (2014-01-01) This tutorial aims to provide a unifying account of current research on diversity and novelty in the domains of web search, recommender systems, and data stream processing.
Diversity and Novelty on the Web: Search, Recommendation, and Data Streaming Aspects Santos, Rodrygo L. T.; Castells, Pablo; Altıngövde, İsmail Sengör; CAN, FAZLI (2015-05-22) This tutorial aims to provide a unifying account of current research on diversity and novelty in different web information systems. In particular, the tutorial will cover the motivations, as well as the most established approaches for producing and evaluating diverse results in search engines, recommender systems, and data streams, all within the context of the World Wide Web. By contrasting the state-of-the-art in these multiple domains, this tutorial aims to derive a common understanding of the diversific...
Knowledge discovery in microarray data of bioinformatics Kocabaş, Fahri Salih; Baykal, Nazife; Department of Health Informatics (2012) This thesis analyzes major microarray repositories and presents a metadata framework both to address the current issues and to promote the main operations such as knowledge discovery, sharing, integration, and exchange. The proposed framework is demonstrated in a case study on real data and can be used for other high throughput repositories in biomedical domain. Not only the number of microarray experimentation increases, but also the size and complexity of the results rise in response to biomedical inquiri...
Learning to rank web data using multivariate adaptive regression splines Altınok, Gülşah; Batmaz, İnci; Karagöz, Pınar; Department of Statistics (2018) A new trend, called learning to rank, has recently come to light in a wide variety of applications in Information Retrieval (IR), Natural Language Processing (NLP), and Data Mining (DM), to utilize machine learning techniques to automatically build the ranking models. Typical applications are document retrieval, expert search, definition search, collaborative filtering, question answering, and machine translation. In IR, there are three approaches used for ranking. The one is traditional model approaches su...
Investigation of haptic line graph comprehension through co production of gesture and language Deniz, Ozan; Mehmetcan, Fal; Acartürk, Cengiz (null; 2013-06-30) In communication settings, statistical graphs accompany language by providing visual access to various aspects of domain entities, such as conveying information about trends. A similar and comparable means for providing perceptual access is to provide haptic graphs for blind people. In this study, we present the results of an experimental study that aimed to investigate visual line graphs and haptic line graphs in time domain by means of gesture production as an indicator of event conceptualization. The par...

Citation Formats

R. L. T. Santos, P. Castells, İ. S. Altıngövde, and F. Can, “Diversity and novelty in information retrieval,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/46230.