Interactive Search Profiles as a Means of Personalisation Maram - - PowerPoint PPT Presentation

Interactive Search Profiles as a Means of Personalisation

Maram Barifah & Monica Landoni Università della Svizzera italiana (USI)

The 2nd Workshop on Evaluation of Personalisation in Information Retrieval (WEPIR 2019) at CHIIR 2019, Glasgow, Scotland, UK, March, 2019

Motivation

• DLs, as information provider platforms, service

heterogeneous users and facilitate knowledge acquisition among users. Users tend to visit DL to fulfill their information needs (IN)

• INs are addressed by the available contents and affected by

the interface design, familiarity and expertise of the users.

• Considering user interactions in the user profiling will

produce more reliable users’ representations.

Motivation

We are:

• Exploring existing interactions by investigating the log

files (LF)

• Proposing ISPs as a means for personalisation

RERO Doc

• It is a Swiss digital library
• The library offers free access to its contents and services. The

login is an option

• The geographical locations of the users are world-wide
• Different items ranging from books and articles to

photographs and sound recordings are available.

http://doc.rero.ch

RERO Doc:

5

RERO Doc result page

More Functions

• search in fulltext or save the the

selected filter for next search

6

• Searchers also can sort the search

results

• Searchers also have the options to look

at similar records, field, or institute

Dataset

7

• The dataset contains the entries of eight-months records from

(May 2017-January 2018) with more than 6 M sessions consisting

• f 24M records of 20 GB
• The long period covers different seasons i.e. before and after

exams, annual holidays, and during the semesters

8

Interface Analysis Data Preparation Building action typology Data Sampling Analytical techniques selection Features Examination Patterns Extraction Patterns Interpretation The Framework of Exploring UPs in LFs

M Barifah, M Landoni : A Framework for Exploring Usage Pattern in Digital Libraries, JCDL 2019, Illinois, USA

9

Satisfied IS (SIS) Multivio IS (MIS) Average IS (AIS) Advance IS (DIS) Item Seekers (IS)

Usage Patterns (UP)s:

Navigators (N) Light N (LN) Average N (AN) Advance N (DN) Press N (PN) Searchers (S) Known item S (KS) Simple S (SS) Average S (AS) Familiar average S (FAS) Advance S (DS) Familiar advance S (FDS) Sophisticated S (PS)

11

ISPs:

• A. Data-driven profiles that depict the types of interaction a

segment of users performs with the system B. Real representations of the users interaction (new and existing users)

• C. A tool can be used by designers for re-evaluation or

redesign the interface.

12

ISPs

13

Interface personalization:

Promoting different search strategies:

• Visualising the search results by applying external thesauri and

suggested terms through machine learning techniques. (Cao et al, 2010, Hajra & Tochtermann, 2018)

• Providing auto completion function, or ”Popular Terms” function. This

might accelerate the searching time for the struggling users. (Kay, 2019)

• Better utilisation of the filter and sort functions (Niu and Hemminger )

Improving navigation experiences:

Providing RERO Doc with navigation icons, Icons are preferable to abstract text as they are easier to memories (Rahrovani, 2017).

Personalization and Design Implementation:

14

• Known item Searcher:

This pattern represents users who usually spend 60 seconds as a maximum duration, search by simple search function, and use the author and keyword facets. Their search usually ends with viewing results page. Out of this pattern, a further ISPs can be constructed with different scenarios e.g.:

• Are KS aware of the facets functionality?
• What are the different paths/ tactics might be suggested?
• What are the tools that might help KS?

Example of an ISP:

Conclusion

• LF analysis reveals valuable information about the user interaction and

their preferences.

• Considering

the interaction might present more reliable users’ representations

• ISPs serve as an input into the redesign and refinement of the interface, and

in general of the functionality of the system.

• ISPs serve the need of iterative evaluations, accounting for new users

coming.

15

16

• A user study will be conducted to validate the LF findings.
• Expert study involving experts in DL design and development.

Future works:

Thank you

Questions?

17

1. Cao, N., Sun, J., Lin, Y.R., Gotz, D., Liu, S., Qu, H.: Facetatlas: Multifaceted vi- sualization for rich text corpora. IEEE transactions on visualization and computer graphics (2010) 1. Hajra, A., Tochtermann, K.: Visual search in digital libraries and the usage of external

• terms. In: 2018 22nd International Conference Information Visualisation (IV) (2018)

2. Kay, J.: Improving access to e-resources for users at the university of derby: enhancing discovery systems with library plus 2.0. Insights (2019) 3. Matusiak, K.K.: User navigation in large-scale distributed digital libraries: The case of the digital public library of america. Journal of Web Librarianship (2017) 4. Rahrovani, S., Mirzabeigi, M., Abbaspour, J.: The trained and untrained users’ mental models compatibility with the icons of search modules in iranian digital library

• applications. Library Hi Tech (2017)

18

References