Temporal Information Retrieval


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How does time affect search?


In the past decade, the Web has evolved in many aspects, such as, its size, content, and usage. With the growing volumes of and reliance on digital documents on the Web, there is a clear need for better information retrieval (IR) approaches that keep relevant information accessible, available, and meaningful over time. In the past decade, time-aware approaches to information retrieval have become interesting, emerging topics and shown that the time dimension affects search performance. In other words, it has been shown that taking the time dimension into account can improve search performance over traditional (non time-aware) IR approaches.

In this course, in the first place, aims to introduce students to the general and wide topic of Web evolution, and then pinpoint a number of issues that is related to temporal aspects of search and IR. We plan to start with an overview of seminal works that shed light on the evolution of Web within time. Next, we will focus on the impacts of this evolution on search and we will essentially focus on indexing of versioned document collections and time-aware retrieval and ranking. We will discuss evolution of search results, and wrap up the course with a review of some recent applications on mining and analytics on temporal web collections.

Schedule


# Date Lecture Links
1 13.10.2014 Introduction Lecture Notes
2 20.10.2014 Foundations-I Lecture Notes
3 27.10.2014 Foundations-II Lecture Notes
4 3.11.2014 Crawling Lecture Notes
5 10.11.2014 Indexing Lecture Notes
6 17.11.2014 Indexing-II Lecture Notes
7 24.11.2014 Compression and QP Lecture Notes
8 1.12.2014 Ranking-I Lecture Notes
9 8.12.2014 Ranking-II Lecture Notes
10 15.12.2014 Evaluation Lecture Notes
11 5.01.2015 Temporal Extraction Lecture Notes
12 12.01.2015 Query Modelling Lecture Notes
13 26.01.2015 Conclusion Lecture Notes

Projects


Students are encouraged to work on projects to test themselves and improve grades. All projects will eventually be merged into our Temporal Search System.

Web Dynamics and Crawling

Temporal Retrieval Models

Indexing of Versioned Documents

Temporal Extraction and Mining