The volume of electronic information that users accumulate is steadily rising. A recent study [2] found that there were on average 32,000 pieces of information (e-mails, web pages, documents, etc.) for each user. The problem of organizin

Dietterich, T. G.

Fitzhenry, E.

Stumpf, S.

English

City Research Online

Stumpf, S., Fitzhenry, E. & Dietterich, T. G. (2007). The use of provenance in information retrieval. Paper presented at the Workshop on Principles of Provenance (PROPR), 19 - 20 November 2007, Edinburgh, Scotland.City Research OnlineOriginal citation: Stumpf, S., Fitzhenry, E. & Dietterich, T. G. (2007). The use of provenance in information retrieval. Paper presented at the Workshop on Principles of Provenance (PROPR), 19 - 20 November 2007, Edinburgh, Scotland.Permanent City Research Online URL: http://openaccess.city.ac.uk/224/ Copyright & reuseCity  University  London has developed City  Research Online  so that  its  users  may access the research outputs of City University London's staff. Copyright © and Moral Rights for this paper are retained by the individual author(s) and/ or other copyright holders. Users may download and/ or print one  copy  of  any  article(s)  in  City  Research  Online  to  facilitate  their  private  study  or  for  non-commercial research. Users may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. All material in City Research Online is checked for eligibility for copyright before being made available in the live archive. URLs from City Research Online may be freely distributed and linked to from other web pages. Versions of researchThe version in City Research Online may differ from the final published version. Users are advised to check the Permanent City Research Online URL above for the status of the paper.EnquiriesIf you have any enquiries about any aspect of City Research Online, or if you wish to make contact  with the author(s) of this paper, please email the team at publications@city.ac.uk.  1The Use of Provenance in Information Retrieval  Simone Stumpf, Erin Fitzhenry, Thomas G. Dietterich Oregon State University Corvallis, OR, USA {stumpf, fitzheer, tgd}@eecs.oregonstate.edu  INTRODUCTION The volume of electronic information that users accumulate is steadily rising. A recent study [2] found that there were on average 32,000 pieces of information (e-mails, web pages, documents, etc.) for each user.  The problem of or-ganizing and retrieving information has given rise to many personal information management (PIM) tools (e.g. [2, 4, 5]). Despite great advances in search technology, information organization and retrieval challenges remain. Users often still navigate manually to retrieve files since generating ap-propriate search terms is difficult, especially when the time gaps between subsequent accesses of documents are large. Recent research [1] has shown that common search criteria, such as creation or modification time, are remembered in-accurately about 50% of the time. Even the title of a docu-ment, the most obvious search criteria, is remembered only partially correct 47% of the time and utterly incorrectly 20% of the time. There may be other document attributes that are more easily remembered by users that could be helpful in re-finding documents. One such attribute is a document’s relationship to other documents [1, 6, 7] but this is not supported in cur-rent tools. We are interested in exploiting document rela-tionships for organizing and re-finding information. PROVENANCE IN DOCUMENT RELATIONSHIPS There have been various definitions of provenance. One common way of viewing provenance is the history or origin of data (e.g. [8]). We view provenance as the history of in-formation between documents: How did two or more sepa-rate documents come to have the same portions of content in common? For example, the following actions could generate docu-ment provenance relationships:  • User copies a range of cells from an Excel document to a Word document.  • User creates a copy of a Word document and modifies the copy. • User receives an email with a Word document attach-ment and saves it to local storage. USING PROVENANCE RELATIONSHIPS  Despite the evidence that provenance relationships could be useful, such information is usually not captured. Current operating systems only store document-specific informa-tion, such as title, location, time, etc. In order to capture re-lationships between documents, tools need to developed that can detect, store and use this type of information. TaskTracer TaskTracer [3] is a PIM tool that allows users to organize and retrieve information based on their activities. The soft-ware combines extensive data collection on user interac-tions, machine learning that leverage this data, and user in-terfaces to assist users in organizing and re-finding informa-tion. Currently, time-stamped user interactions (such as file new, open, print, save, text selection, copy/paste, windows focus, web navigation, email read/send, etc.) are detected in Microsoft Office (Word, Excel, PowerPoint, Internet Ex-plorer, Outlook), the Windows operating system, text and pdf files. Each interaction generates events on information resources (such as files, web pages, emails), which are stored in a database.  Some interactions are special since they produce prove-nance relationships. In TaskTracer, we detect and store the following provenance relationships between resources: Copy/Paste, File Copy, Save As, File Download (from a web page in Internet Explorer), File Upload, Attachment Add, Attachment Save, Attachment Open. (We are in the process of instrumenting Email Reply To/Forward.) Provenance relationships in information retrieval How can these stored provenance relationships help in in-formation organization and retrieval? In our work, we pri-marily address how provenance relationships can assist us-ers in re-finding documents through manual exploration1. A typical use case would be that a user is trying to locate a specific Word document but only remembers an "entry point" in the provenance relationship graph. We have de-veloped a user interface component, TaskTrail (Figure 1), that displays documents and their provenance relationships. In order to see provenance relationships between docu-ments, the user can open TaskTrail from any email, email attachment, or document known to TaskTracer as a re-source. The user interface shows a visual representation of                                                           1 We also intend to investigate information organization by exploring provenance relationships as relational features in clustering for activity discovery.   the entry point document and documents related to it via provenance (Figure 1, left pane), along with all documents contained in the current provenance relationship graph (Figure 1, right pane). The user can open the documents di-rectly from TaskTrail, or explore the graphs further by ex-panding documents' relationships.  We have conducted a preliminary evaluation of the useful-ness of this approach in terms of the amount of document relationships that can be captured. We obtained data from four faculty and student members of the TaskTracer team, covering on average 12.6 days of tracking. On average, each participant had worked with 489.5 information re-sources overall. On average, there were approximately six provenance graphs for each user, containing on average two resources. The majority of these provenance relationships consisted of Copy/Paste relationships, followed by SaveAs relationships. The results of our preliminary evaluation show that it is possible to capture provenance relationships but also point out the challenges of such an approach. In particular, data about provenance relationships need to be captured over a long-term period to be rich enough to be exploited. FUTURE WORK In the future, we would like to explore provenance relation-ships, their graphical representation, and their use for re-finding more deeply. As a first step, we are in the process of collecting long-term data from real-world users.  From a user-perspective, it is important to understand what provenance relationships are considered important. While we have implemented some provenance relationships, it remains to be investigated whether our implementation covers the whole spectrum, and also the role that these rela-tionships play in retrieving documents. Associated with this is how provenance relationship graphs can be visualized to encourage successful exploration. We have designed user studies to answer these questions in order to advance the role of provenance relationships in information retrieval. REFERENCES 1. Blanc-Brude, T, Scapin, DL (2007) What do people re-call about their documents?: implications for desktop search tools. Proc. IUI.  2. Cutrell, E, Robbins, DC, Dumais, S, Sarin, R (2006) Fast, Flexible Filtering with Phlat—Personal Search and Organization Made Easy, Proc. CHI.  3. Dragunov, AN, Dietterich, TG, Johnsrude, K, McLaughlin, M, Li, L, Herlocker, JL (2005) Task-Tracer: a desktop environment to support multi-tasking knowledge workers. Proc. IUI. 4. Dumais, S, Cutrell, E, Cadiz, J, Jancke, G, Sarin, R, Robbins, DC (2003) Stuff I've seen: a system for per-sonal information retrieval and re-use. Proc. SIGIR.  5. Freeman, E, Gelernter, D (1996) Lifestreams: a storage model for personal data. SIGMOD 25, 1. 6. Gonçalves, D, Jorge, JA (2004) Describing documents: what can users tell us?. Proc.IUI . 7. Rothrock, B, Myers, BA, Wang, SH (2006) Unified as-sociative information storage and retrieval. Ext. Ab-stracts CHI. 8. Ludaescher, B (2007) A Quick Tour through the Prove-nance Zoo, PrOPr, Philadelphia, PA, 26 June 2007.  Figure 1. Screenshot of TaskTrail UI showing documents and their provenance relationships. 

The use of provenance in information retrieval

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The use of provenance in information retrieval

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