Stuff I've seen: a system for personal information retrieval and re-use

By Susan T. Dumais, Edward Cutrell, Jonathan J. Cadiz, Gavin Jancke, Raman Sarin, Daniel C. Robbins. Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2003

577 citations recorded by the source corpus.

Subfields: Information Systems and Management, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/daeaf72e3a57f639acc66a398d5fa94c746bf95e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems and Management

In Human-Computer Interaction

Citations in the corpus

Learning to Rank with Selection Bias in Personal Search (2016, background): “Personal search is an important and well studied information retrieval task with applications such as email search [6], desktop search [13], and, most recently, on-device search [23].”
Evaluation of contextual information retrieval effectiveness: overview of issues and research (2010, background): “…data, browsing features [92,108], eye-tracking [57], 2. bookmarks as clues for predicting user preferences [38], 3. desktop information [32] and contextual information sources like news sources (Reuters, New York Times), Blog sites and e-commerce sites [16] used for inferring the user…”
Reference reconciliation in complex information spaces (2005, methodology): “The need for better search tools for the desktop was highlighted by systems like SIS [16] and the Google Desktop search tool [19].”
Semantic Annotation, Indexing, and Retrieval (2003, background): “Another related approach is taken in OFF, [8], which puts an emphasize on the collaborative ontology development and annotation.”
Position Bias Estimation for Unbiased Learning to Rank in Personal Search (2018, background): “Personal search is an important research topic in information retrieval that has been evolving from desktop search [13] to on-device search [21] and more recently to email search [5].”
Personalizing search via automated analysis of interests and activities (2005, methodology): “Such a representation could be obtained from a desktop index such as that described in Stuff I’ve Seen [5] or available in desktop indices such as Copernic, Google Desktop Search, Mac Tiger, Windows Desktop Search, Yahoo! Desktop Search or X1.”
BLINKS: ranked keyword searches on graphs (2007, background): “In personal information management (PIM) systems [8, 4], objects such as emails, documents, and photos are interwoven into a graph using manually or automatically established connections among them.”
Test Collection Based Evaluation of Information Retrieval Systems (2010, unknown): “[79] who as part of the testing of their desktop search engine, Stuff I’ve Seen, deployed a working version of the system, which was installed by 234 users (employees of a large organization) who used the system as their desktop search tool.”
Inducing Ontology from Flickr Tags (2006, background): “[2] have explored faceted search mechanisms, and Hearst [4] and Yee, et al.”
Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing (2012, unknown): “) [217].”
Information re-retrieval: repeat queries in Yahoo's logs (2007, background): “Re-finding behavior has recently attracted consider abl interest [1, 3, 4, 6, 20, 21, 22].”
The Structure of Collaborative Tagging Systems (2005, unknown): “Since finding previously encountered information is extremely important (Dumais et al. 2003), this is deeply problematic for past information.”
Understanding User Behavior Through Log Data and Analysis (2014, background): “, 2008], and compare how different interfaces for supporting email organization influence initial uptake and sustained use [Dumais et al. 2003; Rodden and Leggett, 2010].”
Individual Text Corpora Predict User-Specific Knowledge: Benchmarks of Individualized Knowledge Simulation (2026, unknown): “Internet search behavior provides a promising signal: each visited page reflects active engagement with specific content and contributes to a cumulative personal reading history (Marchionini, 2006; Dumais et al., 2003; Teevan et al., 2007).”