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Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users.

Yoo I, Mosa AS - JMIR Med Inform (2015)

Bottom Line: Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed.To test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5.The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO, United States. yooil@health.missouri.edu.

ABSTRACT

Background: PubMed is the largest biomedical bibliographic information source on the Internet. PubMed has been considered one of the most important and reliable sources of up-to-date health care evidence. Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed. However, very little is known about PubMed users' knowledge of information retrieval (IR) functions and their usage in query formulation.

Objective: The purpose of this study was to shed light on how experienced/nonexperienced PubMed users perform their search queries by analyzing a full-day query log. Our hypotheses were that (1) experienced PubMed users who use system functions quickly retrieve relevant documents and (2) nonexperienced PubMed users who do not use them have longer search sessions than experienced users.

Methods: To test these hypotheses, we analyzed PubMed query log data containing nearly 3 million queries. User sessions were divided into two categories: experienced and nonexperienced. We compared experienced and nonexperienced users per number of sessions, and experienced and nonexperienced user sessions per session length, with a focus on how fast they completed their sessions.

Results: To test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5. The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups.

Conclusions: Experienced PubMed users retrieve relevant documents more quickly than nonexperienced PubMed users in terms of session length.

No MeSH data available.


Query categorization.
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figure2: Query categorization.

Mentions: In order to identify the purpose of user queries for query categorization, we used PubMed’s ATM. Every PubMed user query is automatically translated by ATM to improve overall IR performance and the translated query is actually used for the PubMed search; if a query contains double quotation marks or search tags, those parts (words or terms) are not translated. The ATM translation identifies each term in a query and adds an appropriate search tag to the term. We categorized PubMed queries using ATM-added tags as well as user-added tags after ATM translations. PubMed provides 48 search tags (refer to the PubMed Help website [71] for details), which are classified into informational and navigational tags [69]. Queries containing only informational tags are identified as informational queries. Navigational queries are queries containing navigational or citation-related tags. Queries containing both informational and navigational tags are identified as mixed queries, unless the original query contains an indication of a navigational query. Figure 2 presents a flow diagram for query categorization. A total of 2353 queries resulted in empty query translation. These were removed from the analysis. The translated query texts were then parsed to extract the search tags.


Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users.

Yoo I, Mosa AS - JMIR Med Inform (2015)

Query categorization.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4526974&req=5

figure2: Query categorization.
Mentions: In order to identify the purpose of user queries for query categorization, we used PubMed’s ATM. Every PubMed user query is automatically translated by ATM to improve overall IR performance and the translated query is actually used for the PubMed search; if a query contains double quotation marks or search tags, those parts (words or terms) are not translated. The ATM translation identifies each term in a query and adds an appropriate search tag to the term. We categorized PubMed queries using ATM-added tags as well as user-added tags after ATM translations. PubMed provides 48 search tags (refer to the PubMed Help website [71] for details), which are classified into informational and navigational tags [69]. Queries containing only informational tags are identified as informational queries. Navigational queries are queries containing navigational or citation-related tags. Queries containing both informational and navigational tags are identified as mixed queries, unless the original query contains an indication of a navigational query. Figure 2 presents a flow diagram for query categorization. A total of 2353 queries resulted in empty query translation. These were removed from the analysis. The translated query texts were then parsed to extract the search tags.

Bottom Line: Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed.To test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5.The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO, United States. yooil@health.missouri.edu.

ABSTRACT

Background: PubMed is the largest biomedical bibliographic information source on the Internet. PubMed has been considered one of the most important and reliable sources of up-to-date health care evidence. Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed. However, very little is known about PubMed users' knowledge of information retrieval (IR) functions and their usage in query formulation.

Objective: The purpose of this study was to shed light on how experienced/nonexperienced PubMed users perform their search queries by analyzing a full-day query log. Our hypotheses were that (1) experienced PubMed users who use system functions quickly retrieve relevant documents and (2) nonexperienced PubMed users who do not use them have longer search sessions than experienced users.

Methods: To test these hypotheses, we analyzed PubMed query log data containing nearly 3 million queries. User sessions were divided into two categories: experienced and nonexperienced. We compared experienced and nonexperienced users per number of sessions, and experienced and nonexperienced user sessions per session length, with a focus on how fast they completed their sessions.

Results: To test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5. The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups.

Conclusions: Experienced PubMed users retrieve relevant documents more quickly than nonexperienced PubMed users in terms of session length.

No MeSH data available.