A Complete Year of User Retrieval Sessions in a Social Sciences Academic Search Engine

Mayr, Philipp; Kacem, Ameni

doi:10.1007/978-3-319-67008-9_46

Cited by 6 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Fischer et al (2020) presented a methodology that can be used to analyse data from the transaction log of EBSCO Discovery Service searches recorded in Google Analytics and provided recommendations on improving the quality of Google Analytics functionalities so librarians can gain the most benefit from it. Mayr and Kacem (2017) presented an open data set extracted from the transaction log of the Sowiport social sciences academic search engine. Moreover, they proposed a description of interactions performed by the academic search engine users that can be used in different applications such as result ranking improvement, user modelling, query reformulation analysis and search pattern recognition.…”

Section: Use Analysis Of the Digital Librarymentioning

confidence: 99%

Use analysis of the digital library of PhD dissertations defended at the University of Novi Sad

Paskali

Ivanović

2021

View full text Add to dashboard Cite

Purpose The purpose of this paper is to determine the digital library usage patterns as a means of improving the system, as well as the user experience, to give appropriate recognition to the most popular dissertations’ authors and to measure the interest of non-academic users for dissertations defended at the University of Novi Sad (UNS). Design/methodology/approach A logging module of the digital library of theses and dissertations of University of Novi Sad (PHD UNS) application has been implemented. The module recorded the messages relating to the search queries and downloads over a three-year period from 2017–2019. These logs are analysed using the Elasticsearch, Logstash and Kibana (ELK) technology stack and the results are shown using graphs and tables. Findings The analysis determined the perfect time for weekly maintenance of the system, defined a recommendation for improving the system and revealed the most popular dissertations. A significant number of downloads and queries originated from citizens, i.e. users outside the academic community. Practical implications The conducted analysis defined recommendations for the system improvement which can be used by PHD UNS research and development (R&D) team and revealed the most popular dissertations which are used for the promotion of its authors through faculties’ websites. Originality/value To the best of the authors’ knowledge, this is the first study of ELK based log analysis of a Serbian language documents’ repository. Besides, the value of results for the PHD UNS R&D team and UNS rector team, the study proves that PhD digital library presents an important Open Science communication channel for presenting scientific results to the citizens.

show abstract

Section: Use Analysis Of the Digital Librarymentioning

confidence: 99%

Use analysis of the digital library of PhD dissertations defended at the University of Novi Sad

Paskali

Ivanović

2021

View full text Add to dashboard Cite

show abstract

“…Exploratory search in a DL, especially on the level of browsing, is a frequent strategy when looking for related content [8], [6], [22]. Due to structured metadata that annotate the content of scholarly DLs, users are able to explore the content based on shared characteristics like keywords, classifications, or author information.…”

Section: Introductionmentioning

confidence: 99%

Contextualised Browsing in a Digital Library's Living Lab

Carevic

Schüller

Mayr

et al. 2018

Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries

Self Cite

View full text Add to dashboard Cite

Contextualisation has proven to be effective in tailoring search results towards the users' information need. While this is true for a basic query search, the usage of contextual session information during exploratory search especially on the level of browsing has so far been underexposed in research. In this paper, we present two approaches that contextualise browsing on the level of structured metadata in a Digital Library (DL), (1) one variant bases on document similarity and (2) one variant utilises implicit session information, such as queries and different document metadata encountered during the session of a users. We evaluate our approaches in a living lab environment using a DL in the social sciences and compare our contextualisation approaches against a non-contextualised approach. For a period of more than three months we analysed 47,444 unique retrieval sessions that contain search activities on the level of browsing. Our results show that a contextualisation of browsing significantly outperforms our baseline in terms of the position of the first clicked item in the result set. The mean rank of the first clicked document (measured as mean first relevant -MFR) was 4.52 using a non-contextualised ranking compared to 3.04 when re-ranking the result lists based on similarity to the previously viewed document. Furthermore, we observed that both contextual approaches show a noticeably higher clickthrough rate. A contextualisation based on document similarity leads to almost twice as many document views compared to the non-contextualised ranking.

show abstract

“…http://dx.doi.org/10.7802/1380 and[30] 6 A detailed description of the dataset can be found in[31] 7. The dataset can be downloaded at https://git.gesis.org/amur/SUSS-[16][17] …”

mentioning

confidence: 99%

Analysis of search stratagem utilisation

Kacem

Mayr

2018

Scientometrics

Self Cite

View full text Add to dashboard Cite

In Interactive Information Retrieval, researchers consider the user behaviour towards systems and search tasks in order to adapt search results and to improve the search experience of users. Analysing the users' past interactions with the system is one typical approach. In this paper, we analyse the user behaviour in retrieval sessions towards Marcia Bates' search stratagems such as "Footnote Chasing", "Citation Searching", "Keyword Searching", "Author Searching" and "Journal Run" in a real-life academic search engine. In fact, search stratagems represent high-level search behaviour as the users go beyond simple execution of queries and investigate more of the system functionalities. We performed analyses of these five search stratagems using two datasets extracted from the social sciences search engine sowiport. A specific focus was the detection of the search phase and frequency of the usage of these stratagems. In addition, we explored the impact of these stratagems on the whole search process performance. We addressed mainly the usage patterns' observation of the stratagems, their impact on the conduct of retrieval sessions and explore whether they are used similarly in both datasets. From the observation and metrics proposed, we can conclude that the utilisation of search stratagems in real retrieval sessions leads to an improvement of the precision in terms of positive interactions. For both datasets (SUSS 14-15 and

show abstract

A Complete Year of User Retrieval Sessions in a Social Sciences Academic Search Engine

Cited by 6 publications

References 12 publications

Use analysis of the digital library of PhD dissertations defended at the University of Novi Sad

Use analysis of the digital library of PhD dissertations defended at the University of Novi Sad

Contextualised Browsing in a Digital Library's Living Lab

Analysis of search stratagem utilisation

Contact Info

Product

Resources

About