Adaptive Vague Preference Policy Learning for Multi-round Conversational Recommendation

Conversational recommendation systems (CRS) effectively address information asymmetry by dynamically eliciting user preferences through multi-turn interactions. Existing CRS widely assumes that users have clear preferences. Under this assumption, the agent will completely trust the user feedback and treat the accepted or rejected signals as strong indicators to filter items and reduce the candidate space, which may lead to the problem of over-filtering. However, in reality, users' preferences are often vague and volatile, with uncertainty about their desires and changing decisions during interactions. To address this issue, we introduce a novel scenario called Vague Preference Multi-round Conversational Recommendation (VPMCR), which considers users' vague and volatile preferences in CRS.VPMCR employs a soft estimation mechanism to assign a non-zero confidence score for all candidate items to be displayed, naturally avoiding the over-filtering problem. In the VPMCR setting, we introduce an solution called Adaptive Vague Preference Policy Learning (AVPPL), which consists of two main components: Uncertainty-aware Soft Estimation (USE) and Uncertainty-aware Policy Learning (UPL). USE estimates the uncertainty of users' vague feedback and captures their dynamic preferences using a choice-based preferences extraction module and a time-aware decaying strategy. UPL leverages the preference distribution estimated by USE to guide the conversation and adapt to changes in users' preferences to make recommendations or ask for attributes. Our extensive experiments demonstrate the effectiveness of our method in the VPMCR scenario, highlighting its potential for practical applications and improving the overall performance and applicability of CRS in real-world settings, particularly for users with vague or dynamic preferences

Development of a CT image analysis-based scoring system to differentiate gastric schwannomas from gastrointestinal stromal tumors

PurposeTo develop a point-based scoring system (PSS) based on contrast-enhanced computed tomography (CT) qualitative and quantitative features to differentiate gastric schwannomas (GSs) from gastrointestinal stromal tumors (GISTs).MethodsThis retrospective study included 51 consecutive GS patients and 147 GIST patients. Clinical and CT features of the tumors were collected and compared. Univariate and multivariate logistic regression analyses using the stepwise forward method were used to determine the risk factors for GSs and create a PSS. Area under the receiver operating characteristic curve (AUC) analysis was performed to evaluate the diagnostic efficiency of PSS.ResultsThe CT attenuation value of tumors in venous phase images, tumor-to-spleen ratio in venous phase images, tumor location, growth pattern, and tumor surface ulceration were identified as predictors for GSs and were assigned scores based on the PSS. Within the PSS, GS prediction probability ranged from 0.60% to 100% and increased as the total risk scores increased. The AUC of PSS in differentiating GSs from GISTs was 0.915 (95% CI: 0.874–0.957) with a total cutoff score of 3.0, accuracy of 0.848, sensitivity of 0.843, and specificity of 0.850.ConclusionsThe PSS of both qualitative and quantitative CT features can provide an easy tool for radiologists to successfully differentiate GS from GIST prior to surgery

Requirement elicitation for enterprise information systems : a process based on meta-model of Zachman framework developed using ontologies

An enterprise information system distinguishes itself from other types of software as it is developed to facilitate the operation of an organization hence its requirement reflects its strategies, plans, organizations, processes, marketing etc. We believe that the requirements in the form of domain knowledge acquired in the early stage of system development can be organized and modeled in an Enterprise Architecture. Zachman Framework is one of the most widely used Enterprise Architectures Framework. However, in the original version of the Zachman Framework, there is neither a rigorous meta-model nor a well-defined sequence in which to instantiate the cells, which prevents it from being used practically during the requirement engineering phase of an enterprise information system project. To improve such a situation we develop a conceptual meta-model for the Zachman Framework by adapting and integrating the Bunge-Wand-Weber ontology and the Enterprise Ontology. Based on this meta-model, various requirement acquisition processes can be formulated by specifying a sequence to traverse the meta-model graph and instantiate its nodes and edges. In this thesis we present such a process, suitable for an enterprise system development project of a particular situation

Requirement analysis for enterprise information systems:developing an ontological meta-model for Zackman Framework

An enterprise information system distinguishes itself from other types of software as it is developed to facilitate the operation of an organization hence its requirement reflects its strategies, plans, organizations, processes, marketing etc. We believe that the requirements in the form of domain knowledge acquired in the early stage of system development can be organized and modeled in an Enterprise Architecture. Zachman Framework is one of the most widely used Enterprise Architectures. However, in the original version of the Zachman Framework, there is neither a rigorous meta-model nor a well-defined sequence in which to instantiate the cells, which prevents it from being used practically during the requirement engineering phase of an enterprise information system project. To improve such a situation we develop a conceptual meta-model for the Zachman Framework by adapting and integrating the Bunge-Wand-Weber ontology and the Enterprise Ontology. Based on this meta-model, various requirement acquisition processes can be formulated by specifying a sequence to traverse the meta-model graph and instantiate its nodes and edges. In this paper we present such a process, suitable for an enterprise system development project of a particular situation

Temporomandibular joint disc repositioning using bone anchors: an immediate post surgical evaluation by Magnetic Resonance Imaging

Abstract Background Open joint procedures using bone anchors have shown clinical and radiograph good success, but post surgical disc position has not been documented with MRI imaging. We have designed a modified technique of using two bone anchors and 2 sutures to reposition the articular discs. This MRI study evaluates the post surgical success of this technique to reposition and stabilize the TMJ articular discs. Methods Consecutive 81 patients with unilateral TMJ internal derangement (ID) (81 TMJs) were treated between December 1, 2003, and December 1, 2006, at the Department of Oral and Maxillofacial Surgery, Ninth Peoples Hospital, Shanghai, Jiao Tong University School of Medicine. All patients were subjected to magnetic resonance imaging before and one to seven days post surgery to determine disc position using the modified bone anchor technique. Results Postoperative MRIs (one to seven days) confirm that 77 of 81 joints were identified as excellent results and one joint was considered good for an overall effective rate of 96.3% (78 of 81 joints). Only 3.7% (3 of 81) of the joints were designated as poor results requiring a second open surgery. Conclusions This procedure has provided successful repositioning of the articular discs in unilateral TMJ ID at one to seven days post surgery.</p