A Personalized and Scalable Machine Learning-Based File Management System

In this work, we present a hybrid image and document filing system that we have built. When a user wants to store a file in the system, it is processed to generate tags using an appropriate open-source machine learning system. Presently, we use OpenCV and Tesseract OCR for tagging files. OpenCV recognizes objects in the images and TesserAct recognizes text in the image. An image file is processed for object recognition using OpenCV as well for text/captions process using TesserAct, which are used for tagging the file. All other files are processed using Tesseract only for generating tags. The user can also enter their own tags. A database system has been built that stores tags and the image path. Every file is stored with its owner identification and it is time-stamped. The system has a client-server architecture and can be used for storing and retrieving a large number of files. This is a highly scalable system

Investigating the Effect of Familiarity with Target Document on Retrieval Success in Group Information Repositories

system they are not familiar with in order to retrieve a file they were told about (for example, a new member of an organization who has to fill out a form may be instructed to look for a template on the organization’s network drive). This individual may encounter difficulties finding the file or experience frustration during the process, as their incomplete knowledge of where the file is in the folder hierarchy or how to start looking for it may lead them to spend a lot of time looking in the wrong places or trying to ‘work out’ where the most likely location of the file might be. The purpose of this study is to investigate the factors influencing how successfully and effectively a user is able to retrieve a file from a shared information repository when they may not be fully aware of its contents or location. The re-finding context was a desktop hierarchical folder structure linked to a cloud-based group information repository (Dropbox). RQ1: How does familiarity with the retrieval target influence retrieval success and retrieval efficiency? o Hypothesis: Familiarity with the retrieval target is positively correlated with retrieval success and retrieval efficiency. RQ2: What are common characteristics of re-finding experiences in shared folders? In this study, an elicited personal information retrieval method (detailed in the Literature Review and Section 3.2) is used in conjunction with qualitative methods; as the quantitative data obtained on retrieval outcomes can be linked to the qualitative data gathered from the same participants, this procedure generates explanatory in addition to descriptive information.Bachelor of Scienc

Why do some people search for their files much more than others? A preliminary study

Purpose: Previous research has repeatedly shown that people only search for files in a small minority of cases when they do not remember the file's location. The current study aimed to examine whether there is a group of hyper-searchers who search significantly more than others. Based on previous neurocognitive studies, this study aims to hypothesize that if such a group exists, they will have superior verbal memory and reduced visuospatial memory. Design/methodology/approach: In total, 65 participants completed a questionnaire estimating their search percentages, as well as reporting demographic data. Verbal memory was measured using the Wechsler logical memory test, and visuospatial memory was assessed using an online card memory game. Findings: Hyper-searchers were defined as participants with search percentage of over one standard deviation (SD) above the mean. The average search percentage of the seven participants who met this criterion was 51% (SD = 14%), over five times more than the other participants (M = 10%, SD = 9%). Similar results were obtained by re-analyzing data from four previous papers (N = 1,252). The results further confirmed the hypothesis that hyper-searchers have significantly better verbal memory than other participants, possibly making searching easier and more successful for them. Lastly, the search percentage was positively predicted by verbal memory scores and negatively predicted by visuospatial memory scores. Explanations and future research are discussed. Originality/value: This preliminary study is the first to introduce the concept of hyper-searchers, demonstrate its existence and study its causes