論文 / 著書情報
Article / Book Information
Title

A Method for Searching Keyword-lacking Files Based on Interfile
Relationships

AuthorTetsutaro Watanabe, Takashi Kobayashi, Haruo Yokota

Journal/Book nameProc. of 16th Intl Conf. Cooperative Information Systems(CoopIS2008),, , pp. 14-15

発行日 / Issue date2008, 11DOI

10.1007/978-3-540-88875-8̲7

権利情報 / Copyright

The original publication is available at www.springerlink.com.

Note

このファイルは著者（最終）版です。
This file is author (final) version.

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A Method for Searching Keyword-lacking Files Basedon Interfile Relationships
Tetsutaro Watanabe1 , Takashi Kobayashi2 , and Haruo Yokota1
1

Grad. School of Information Science and Engineering, Tokyo Institute of Technology, Japan{tetsu@de., yokota@}cs.titech.ac.jp
2Grad. School of Information Science, Nagoya University, Japan
tkobaya@is.nagoya-u.ac.jp
Abstract. Traditional full-text searches cannot search keyword-lacking files, even
if the files are related to the keywords. In this paper, we propose a method forsearching keyword-lacking files named FRIDAL (File Retrieval by Interfile relationships Derived from Access Logs). The proposed method derives interfile
relationship information from file access logs in the file server, based on the concept that those files opened by a user in a particular time period are related.

1 Introduction
Advances in information technologies have led to many types of multimedia data being
stored as files in computer systems alongside conventional textual material. Moreover,
the recent price drop for magnetic disk drives has accelerated the explosive increasein the number of files within typical file systems [1]. To find a desired file located ata deep node in the directory tree, several desktop search tools using full-text searchtechniques have been developed. However, their target is restricted to text-based files
such as Office documents, PDFs, and emails. Other types of files, such as image files
and data files, cannot be found by these full-text search tools because they lack search
keywords. Even for text-based files, they cannot be found if they do not include directlyrelated keywords. It becomes even harder if these files are located in different directories
from the files that contain the keywords.
To address the demand for searching for these keyword-lacking files, we focus on
the relationship between files that have been frequently accessed at about the sametime. Although several researches for deriving interfile relationship from system call/OS
event logs have been proposed[2, 3], these methods need to modify OS of target systems
and/or to install custom plugins and did not consider detail access patterns of target files.
In this paper, we propose a method for mining the file access logs in a file server
to find interfile relationships and for searching keyword-lacking files that match withgiven keywords by using interfile relationships.

2Proposed Method

First, we extract FUD (File Use Duration) of each files as the time between open-fileand close-file from the file access logs. However, the actual duration of file use differsfrom the FUD because several applications do not keep file opened while using it and/or
a user sometimes leaves his or her seat with files open.

IIAFUDs of each file
f1
f2

p1

c1

AFUD

t1

c2

p3
c3

(10)
20

( TF-IDF point )Total point

0.5+10(30)3025t2t3

Fig. 1. Calculation of relationship elements+15
Keyword-lacking
related filef2

1.00.75

d23AFUD+5f 3 (20)d12p2time

f4

AFUDAFUDAFUDResults of full-text search

CO between
f 1 and f 2f1(0)45+30Weight ofrelationshipFig.2. Calculation of the point of files.

In our proposed method, we prepare the File Type List to indicate which application
keep file opened and calculate the Active Time List from the file access log. By using
above two information, we extract AFUD(Approximate FUD) of each files.
We assume that strongly related files are used at the same time when executing
the same task. To express this relationship, we introduce four “relationship elements”,
where the term “CO” (co-occurrence) is defined as the overlap of two AFUDs; T (Totaltime of COs), C (Number of COs), D (Total time of the time span between COs) andP (Similarity of the timings of the open-file operations). Fig 1. shows how we calculate
each elements. By using these four relationship elements, we define the weight of interfile relationship as follows: R(fi , fj ) = T α · C β · Dγ · P δ . Finally we calculate file
point of fi by adding tf.idf point of fj in proportion to the normalized R(fi , fj ) (Fig.2).

3Conclusion

This paper presents a method for searching for files that lack keywords but do have anassociation with them. The proposed method derives interfile relationship by extracting
AFUD of each files and calculating four “relationship elements” from AFUDs.
Although we cannot describe details due to limitations of space, we have implemented the proposed method FRIDAL as an experimental system. It can mines theinterfile relationships from the access logs of Samba and performs the file point calculations by using interfile relationships and a full-text search engine, Hyper Estraier.
We also have evaluated its effectiveness by experiments. We have compared thesearch results for FRIDAL with a full-text search method, directory search method anda method used in Connections[2]. The experiment showed FRIDAL is superior to othermethods in the 11-points precision and the recall/precision of the top 20.

References
1. N. Agrawal, W. J. Bolosky, J. R. Douceur and J. R. Lorch: A Five-Year Study of File-System
Metadata. ACM Trans. on Storage Vol.3, Iss.3, No.9 (2007)
2. C. A. N. Soules, and G. R. Ganger: Connections: using context to enhance file search. Proc.
SOSP’05, pp.119-132 (2005)
3. R. Ohsawa, K. Takashio, H. Tokuda: OreDesk: A Tool for Retrieving Data History Based onUser Operations, Proc. ISM’06, pp. 762-765 (2006)