Recommendation Seeking Behavior: Empirical Study of Recommendation Needs in Everyday Life

This study explores why recommendation seekers look for recommendations, and how they interact with recommendations through their social milieu. This study utilizes qualitative one-week diary recordings and post-diary interviews to collect rich data that reflect recommendation seekers’ interaction and evaluation strategies in real life issues. The results show that respondents needed recommendations when they are new to situation, wish for changes from a routine behavior, seek trustworthy options or better solutions, and need inspiration. Degree of recommenders’ understanding participants’ situation is more significant than that of sharing interest and similarity with recommenders

Query Resolution for Conversational Search with Limited Supervision

In this work we focus on multi-turn passage retrieval as a crucial component of conversational search. One of the key challenges in multi-turn passage retrieval comes from the fact that the current turn query is often underspecified due to zero anaphora, topic change, or topic return. Context from the conversational history can be used to arrive at a better expression of the current turn query, defined as the task of query resolution. In this paper, we model the query resolution task as a binary term classification problem: for each term appearing in the previous turns of the conversation decide whether to add it to the current turn query or not. We propose QuReTeC (Query Resolution by Term Classification), a neural query resolution model based on bidirectional transformers. We propose a distant supervision method to automatically generate training data by using query-passage relevance labels. Such labels are often readily available in a collection either as human annotations or inferred from user interactions. We show that QuReTeC outperforms state-of-the-art models, and furthermore, that our distant supervision method can be used to substantially reduce the amount of human-curated data required to train QuReTeC. We incorporate QuReTeC in a multi-turn, multi-stage passage retrieval architecture and demonstrate its effectiveness on the TREC CAsT dataset.Comment: SIGIR 2020 full conference pape

Examining Users’ Knowledge Change in the Task Completion Process

This paper examines the changes of information searchers’ topic knowledge levels in the process of completing information tasks. Multi-session tasks were used in the study, which enables the convenience of eliciting users’ topic knowledge during their process of completing the whole tasks. The study was a 3-session laboratory experiment with 24 participants, each time working on one subtask in an assigned 3-session general task. The general task was either parallel or dependently structured. Questionnaires were administered before and after each session to elicit users’ perceptions of their knowledge levels, task attributes, and other task features, for both the overall task and the sub-tasks. Our results support the assumption that users’ knowledge generally increases after each search session, but there were exceptions in which a “ceiling” effect was shown. We also found that knowledge was correlated with users’ perceptions of task attributes and accomplishment. In addition, task type was found to affect several aspects of knowledge levels and knowledge change. These findings further our understanding of users’ knowledge in information tasks and are thus helpful for information retrieval research and system design

Contextualised Browsing in a Digital Library's Living Lab

Contextualisation has proven to be effective in tailoring \linebreak search results towards the users' information need. While this is true for a basic query search, the usage of contextual session information during exploratory search especially on the level of browsing has so far been underexposed in research. In this paper, we present two approaches that contextualise browsing on the level of structured metadata in a Digital Library (DL), (1) one variant bases on document similarity and (2) one variant utilises implicit session information, such as queries and different document metadata encountered during the session of a users. We evaluate our approaches in a living lab environment using a DL in the social sciences and compare our contextualisation approaches against a non-contextualised approach. For a period of more than three months we analysed 47,444 unique retrieval sessions that contain search activities on the level of browsing. Our results show that a contextualisation of browsing significantly outperforms our baseline in terms of the position of the first clicked item in the result set. The mean rank of the first clicked document (measured as mean first relevant - MFR) was 4.52 using a non-contextualised ranking compared to 3.04 when re-ranking the result lists based on similarity to the previously viewed document. Furthermore, we observed that both contextual approaches show a noticeably higher click-through rate. A contextualisation based on document similarity leads to almost twice as many document views compared to the non-contextualised ranking.Comment: 10 pages, 2 figures, paper accepted at JCDL 201

Inferring User Knowledge Level from Eye Movement Patterns

The acquisition of information and the search interaction process is influenced strongly by a person’s use of their knowledge of the domain and the task. In this paper we show that a user’s level of domain knowledge can be inferred from their interactive search behaviors without considering the content of queries or documents. A technique is presented to model a user’s information acquisition process during search using only measurements of eye movement patterns. In a user study (n=40) of search in the domain of genomics, a representation of the participant’s domain knowledge was constructed using self-ratings of knowledge of genomics-related terms (n=409). Cognitive effort features associated with reading eye movement patterns were calculated for each reading instance during the search tasks. The results show correlations between the cognitive effort due to reading and an individual’s level of domain knowledge. We construct exploratory regression models that suggest it is possible to build models that can make predictions of the user’s level of knowledge based on real-time measurements of eye movement patterns during a task session

09101 Abstracts Collection -- Interactive Information Retrieval

From 01.03. to 06.03.2009, the Dagstuhl Seminar 09101 ``Interactive Information Retrieval \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Understanding What Personal Information Items Make Categorization Difficult

ABSTRACT This study examined personal information items that are difficult to categorize, and how people deal with these information items. For this research study, 18 participants were asked to keep a diary over a week and record diary entries whenever they decided to save or organize any electronic personal information items. Then, two post-diary semi-structured interviews were conducted to ask questions about how they organized their information items and why they made such decisions based on the diary they kept. Interviews were analyzed by using a grounded theory approach. The results show that the information items that are ambiguous or anomalous are difficult to categorize. Participants dealt with ambiguous or anomalous information items by categorizing them into one of their existing categories, placing them into a miscellaneous category or revising the existing organizational structure. Since personal information items that are difficult to categorize directly influence the time and effort needed to organize personal information, it is important to understand what kind of personal information items makes personal information organization difficult. In particular, the results of this research study have practical implications in developing interfaces and applications that help organizing personal information items effectively. This study also helps us further understand categorization, information organizing behavior, and personal information management