48,888 research outputs found
Ranking algorithms for implicit feedback
This report presents novel algorithms to use eye movements as an implicit relevance feedback in order to improve the performance of the searches. The algorithms are evaluated on "Transport Rank Five" Dataset which were previously collected in Task 8.3. We demonstrated that simple linear combination or tensor product of eye movement and image features can improve the retrieval accuracy
Case Adaptation with Qualitative Algebras
This paper proposes an approach for the adaptation of spatial or temporal
cases in a case-based reasoning system. Qualitative algebras are used as
spatial and temporal knowledge representation languages. The intuition behind
this adaptation approach is to apply a substitution and then repair potential
inconsistencies, thanks to belief revision on qualitative algebras. A temporal
example from the cooking domain is given. (The paper on which this extended
abstract is based was the recipient of the best paper award of the 2012
International Conference on Case-Based Reasoning.
Design of the software development and verification system (SWDVS) for shuttle NASA study task 35
An overview of the Software Development and Verification System (SWDVS) for the space shuttle is presented. The design considerations, goals, assumptions, and major features of the design are examined. A scenario that shows three persons involved in flight software development using the SWDVS in response to a program change request is developed. The SWDVS is described from the standpoint of different groups of people with different responsibilities in the shuttle program to show the functional requirements that influenced the SWDVS design. The software elements of the SWDVS that satisfy the requirements of the different groups are identified
Identifying and Exploiting Features for Effective Plan Retrieval in Case-Based Planning
Case-Based planning can fruitfully exploit knowledge
gained by solving a large number of problems, storing
the corresponding solutions in a plan library and reusing
them for solving similar planning problems in the future.
Case-based planning is extremely effective when
similar reuse candidates can be efficiently chosen.
In this paper, we study an innovative technique based
on planning problem features for efficiently retrieving
solved planning problems (and relative plans) from
large plan libraries. A problem feature is a characteristic
of the instance that can be automatically derived from
the problem specification, domain and search space
analyses, and different problem encodings.
Since the use of existing planning features are not always
able to effectively distinguish between problems
within the same planning domain, we introduce a new
class of features.
An experimental analysis in this paper shows that our
features-based retrieval approach can significantly improve
the performance of a state-of-the-art case-based
planning system
Automated user modeling for personalized digital libraries
Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to
improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in
an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information
Using Information Filtering in Web Data Mining Process
Web service-oriented Grid is becoming a standard for achieving loosely coupled distributed computing. Grid services could easily be specified with web-service based interfaces. In this paper we first envisage a realistic Grid market with players such as end-users, brokers and service providers participating co-operatively with an aim to meet requirements and earn profit. End-users wish to use functionality of Grid services by paying the minimum possible price or price confined within a specified budget, brokers aim to maximise profit whilst establishing a SLA (Service Level Agreement) and satisfying end-user needs and at the same time resisting the volatility of service execution time and availability. Service providers aim to develop price models based on end-user or broker demands that will maximise their profit. In this paper we focus on developing stochastic approaches to end-user workflow scheduling that provides QoS guarantees by establishing a SLA. We also develop a novel 2-stage stochastic programming technique that aims at establishing a SLA with end-users regarding satisfying their workflow QoS requirements. We develop a scheduling (workload allocation) technique based on linear programming that embeds the negotiated workflow QoS into the program and model Grid services as generalised queues. This technique is shown to outperform existing scheduling techniques that don't rely on real-time performance information
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Teaching and learning in information retrieval
A literature review of pedagogical methods for teaching and learning information retrieval is presented. From the analysis of the literature a taxonomy was built and it is used to structure the paper. Information Retrieval (IR) is presented from different points of view: technical levels, educational goals, teaching and learning methods, assessment and curricula. The review is organized around two levels of abstraction which form a taxonomy that deals with the different aspects of pedagogy as applied to information retrieval. The first level looks at the technical level of delivering information retrieval concepts, and at the educational goals as articulated by the two main subject domains where IR is delivered: computer science (CS) and library and information science (LIS). The second level focuses on pedagogical issues, such as teaching and learning methods, delivery modes (classroom, online or e-learning), use of IR systems for teaching, assessment and feedback, and curricula design. The survey, and its bibliography, provides an overview of the pedagogical research carried out in the field of IR. It also provides a guide for educators on approaches that can be applied to improving the student learning experiences
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