[논문]이미지 기반 디지털 도서관에서 이용자 검색 패턴의 효과적 이해를 위한 트랜잭션 로그 데이터 분석

Han, Hye-Jung; Joo, Soohyung; Wolfram, Dietmar

doi:10.14699/kbiblia.2014.25.1.019

이미지 기반 디지털 도서관에서 이용자 검색 패턴의 효과적 이해를 위한 트랜잭션 로그 데이터 분석
Using Transaction Logs to Better Understand User Search Session Patterns in an Image-based Digital Library 원문보기

한국비블리아학회지 = Journal of the Korean Biblia Society for Library and Information Science, v.25 no.1, 2014년, pp.19 - 37

Han, Hye-Jung (School of Information Studies, University of Wisconsin-Milwaukee) , Joo, Soohyung (School of Information Studies, University of Wisconsin-Milwaukee) , Wolfram, Dietmar (School of Information Studies, University of Wisconsin-Milwaukee)

초록
AI-Helper

본 연구는 이미지 기반 디지털 도서관의 이용자 검색 패턴을 효과적으로 분석하기 위해 이용자 검색 로그 데이터를 분석하였다. 기술 통계와 네트워크 분석 방법을 사용하여 한 달간 수집한 트랜잭션 로그 데이터를 분석하였다. 연구 결과는 이용자들이 특정 주제 내에서 검색 결과 보기와 이미지 아이템 평가를 반복적으로 수행하고 있음을 밝혀내었다. 본 연구는 이미지 자료 검색의 로그 분석을 위해 복합적 데이터 분석 방법을 이용하였다는 점에 의의가 있다.

Abstract ▼ AI-Helper

Server transaction logs containing complete click-through data from a digital library of primarily image-based documents were analyzed to better understand user search session behavior. One month of data was analyzed using descriptive statistics and network analysis methods. The findings reveal iterative search behaviors centered on result views and evaluation and topical areas of focus for the search sessions. The study is novel in its combined analytical techniques and use of click-through data for image collections.

주제어

AI 본문요약
AI-Helper

* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

문제 정의

The findings of this study have implications for understanding search behavior and DL design for image collections. The findings reveal that users request search results and individual item view pages most frequently while relatively fewer numbers of actions were related to query creation and reformulation.
This study is novel in that it investigates users’ search actions, especially transitions in those actions, in an image-based digital library.

가설 설정

4) Are there differences in query patterns between queries submitted internal to the digital collections and those originating from outside the collections, such as search engines?

제안 방법

In this study we have attempted to uncover unique search patterns in image-based collections by analyzing click-through transaction log data in an unobtrusive manner, including queries submitted by internal and external users of an image-based digital library, an IR environment that has not been widely studied to date. The use of transaction log data has provided a larger data set to study than direct observation would permit.
Table 3 summarizes the 30 most frequent query terms from the external queries and the internal queries, respectively. Since one of the purposes of this study is to explore term frequency patterns, all observed words were included in the analysis, including grammatical words (e.g., articles, conjunctions, prepositions) such as the, of, and and a. Although these types of terms could be viewed as stop words by an IR system for indexing and retrieval purposes, they more accurately reflect user input and search intentions.
These studies have revealed that interactions with public search services such as search engines are generally brief with little browsing of results and modification of findings (Spink, Wolfram, Jansen, and Saracevic 2001; Jansen, Spink, and Koshman 2007; Markey 2007; Jansen, Booth, and Spink 2009). These studies have also focused primarily on query-related data and not on the full click-through data of transaction logs, i.e., actions related to all aspects of the information seeking process, including search results and related actions taken by users. The present research is prompted by the desire to determine if the findings regarding user interactions for public search services are similar for digital libraries (DLs) where, unlike general search engines, users will rely on specialized document collections, such as image collections, for specific purposes.

대상 데이터

The University of Wisconsin-Milwaukee libraries house a digital library consisting of approximately 30 digitized visual collections. The collections comprise more than 54,000 photographic images and maps. In particular, the selected digital library has specialized collections of regional archives that address Milwaukee history, Milwaukee neighborhoods, and University of Wisconsin-Milwaukee-related archives.

이론/모형

Before the inflection point, two adjacent actions were considered to occur in the same session. As the distribution is non-linear, Kernel regression was applied using MATLAB to find the inflection point. Kernel regression is a non-parametric estimation method to predict the conditional expectation of a random variable (Shawe-Taylor and Cristianini 2004).
In this study, an Epanechnikov kernel was selected as a weight function (Li and Racine 2007), while the bandwidth was calculated based on Silverman’s rule (Silverman 1986).

성능/효과

The results revealed that users showed successful image retrieval on the Web with short queries while users’ failed searches for images were associated with longer queries.

후속연구

This, however, was not the purpose of the present study. Future research could combine direct observation and interaction with users of the digital collections to better understand their intentions.

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상세보기

저자의 다른 논문 :

표제어: PCR

동의어: Packet Collision Rate

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용어 설명: PCR은 세균 특이성이 있는 primer를 이용하여 적은 수의 세균이 있을지라도 쉽게 검출할 수 있는 유용한 방법이며, 이를 이용하여 구강 내 치면세균막이나 타액에서 직접 세균을 검출할 수 있게 되었다[8].

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 논문명, 저널/프로시딩명, 저자 , 발행년, 권, 호, 시작페이지, 끝페이지, 발행기관 관리번호, 논문명, 대등논문명, 저자 , 저널/프로시딩명, 발행기관, 발행년, 발행언어, 권, 호, 시작페이지, 끝페이지, ISBN, ISSN, 주제분야, 키워드, 초록(한글), 초록(영문), 저자(소속기관)
저장형식	Text(ASCII format) Excel format RefWorks Direct Export RIS format (for Reference Manager, ProCite, EndNote), Scholar's Aids, Mendeley
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

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