Enriching semantic search with preference and quality scores

2017 ◽  
Vol 01 (01) ◽  
pp. 1650002
Author(s):  
Michele Missikoff ◽  
Anna Formica ◽  
Elaheh Pourabbas ◽  
Francesco Taglino
Keyword(s):  
Search Space ◽  
Search Method ◽  
Semantic Search ◽  
Conceptual Similarity ◽  
Web Information ◽  
User Request ◽  
Reference Ontology ◽  
Web Information Systems ◽  
Searching Method

This paper proposes an advanced searching method, aimed at improving Web Information Systems by adopting semantic technology solutions. In particular, it first illustrates the main solutions for semantic search and then proposes the semantic search method [Formula: see text] that represents an evolution of the original SemSim method. The latter is based on the annotation of the resources in a given search space by means of Ontology Feature Vectors ([Formula: see text]), built starting from a reference ontology. Analogously, a user request is expressed as a set of keywords (concepts) selected from the reference ontology, that represent the desired characteristics of the searched resources. Then, the searching method consists in extracting the resources having the [Formula: see text] that exhibit the highest conceptual similarity to the user request. The new method, [Formula: see text], improves the above mechanism by enriching the [Formula: see text] with scores. In the user request, a score (High, Medium, Low) is associated with a concept and indicates the preference (i.e., the priority) that the user assigns to the different concepts in searching for resources. In the resource annotation, the score indicates the level of quality of the concept used to characterize the resource. The [Formula: see text] method has been experimented and the results show that it outperforms the SemSim method and, therefore, also the most representative similarity methods proposed in the literature, as already shown in previous works of the authors.

scholarly journals Semantic Search Enhanced with Rating Scores

2020 ◽  
Vol 12 (4) ◽  
pp. 67
Author(s):  
Anna Formica ◽  
Elaheh Pourabbas ◽  
Francesco Taglino
Keyword(s):  
Semantic Similarity ◽  
Semantic Search ◽  
Digital Resources ◽  
User Request ◽  
Reference Ontology ◽  
Better Than

This paper presents SemSime, a method based on semantic similarity for searching over a set of digital resources previously annotated by means of concepts from a weighted reference ontology. SemSime is an enhancement of SemSim and, with respect to the latter, it uses a frequency approach for weighting the ontology, and refines both the user request and the digital resources with the addition of rating scores. Such scores are High, Medium, and Low, and in the user request indicate the preferences assigned by the user to each of the concepts representing the searching criteria, whereas in the annotation of the digital resources they represent the levels of quality associated with each concept in describing the resources. The SemSime has been evaluated and the results of the experiment show that it performs better than SemSim and an evolution of it, referred to as S e m S i m R V .

scholarly journals Video Caption Based Searching Using End-to-End Dense Captioning and Sentence Embeddings

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 992
Author(s):  
Akshay Aggarwal ◽  
Aniruddha Chauhan ◽  
Deepika Kumar ◽  
Mamta Mittal ◽  
Sudipta Roy ◽  
...  
Keyword(s):  
Search Space ◽  
Video Content ◽  
Video Captioning ◽  
The Past ◽  
Percentile Score ◽  
Universal Sentence ◽  
End To End ◽  
Video Searching ◽  
Searching Method

Traditionally, searching for videos on popular streaming sites like YouTube is performed by taking the keywords, titles, and descriptions that are already tagged along with the video into consideration. However, the video content is not utilized for searching of the user’s query because of the difficulty in encoding the events in a video and comparing them to the search query. One solution to tackle this problem is to encode the events in a video and then compare them to the query in the same space. A method of encoding meaning to a video could be video captioning. The captioned events in the video can be compared to the query of the user, and we can get the optimal search space for the videos. There have been many developments over the course of the past few years in modeling video-caption generators and sentence embeddings. In this paper, we exploit an end-to-end video captioning model and various sentence embedding techniques that collectively help in building the proposed video-searching method. The YouCook2 dataset was used for the experimentation. Seven sentence embedding techniques were used, out of which the Universal Sentence Encoder outperformed over all the other six, with a median percentile score of 99.51. Thus, this method of searching, when integrated with traditional methods, can help improve the quality of search results.

Patterns for Improving the Pragmatic Quality of Web Information Systems

2011 ◽  
pp. 57-70
Author(s):  
Pankaj Kamthan
Keyword(s):  
Information Systems ◽  
Quality Attributes ◽  
Architecture Design ◽  
Web Information ◽  
Web Information Systems

The significance of approaching Web information systems (WIS) from an engineering viewpoint is emphasized. A methodology for deploying patterns as means for improving the quality of WIS as perceived by their stakeholders is presented. In doing so, relevant quality attributes and corresponding stakeholder types are identified. The role of a process, feasibility issues, and the challenges in making optimal use of patterns are pointed out. Examples illustrating the use of patterns during macro- and micro-architecture design of a WIS, with the purpose of the improvement of quality attributes, are given.

Towards the Adaptive Web Using Metadata Evolution

2011 ◽  
pp. 286-300
Author(s):  
Nicolas Guelfi ◽  
Cédric Pruski ◽  
Chantal Reynaud
Keyword(s):  
Information Systems ◽  
Semantic Web ◽  
Web Data ◽  
Survey Techniques ◽  
Web Information ◽  
Web Use ◽  
Web Information Systems ◽  
Data Evolution ◽  
The Web

The evolution of Web information is of utmost importance in the design of good Web Information Systems applications. New emerging paradigms, like the Semantic Web, use ontologies for describing metadata and are defined, in part, to aid in Web evolution. In this chapter, we survey techniques for ontology evolution. After identifying the different kinds of evolution with which the Web is confronted, we detail the various existing languages and techniques devoted to Web data evolution, with particular attention to Semantic Web concepts, and how these languages and techniques can be adapted to evolving data in order to improve the quality of Web Information Systems applications.

Towards Quality Web Information Systems Through Precise Model-Driven Development

2011 ◽  
pp. 344-362
Author(s):  
Fernando Molina ◽  
Francisco J. Lucas ◽  
Ambrosio Toval Alvarez ◽  
Juan M. Vara ◽  
Paloma Cáceres ◽  
...  
Keyword(s):  
Information Systems ◽  
Formal Specification ◽  
Verification And Validation ◽  
The Internet ◽  
Formal Approach ◽  
Model Driven ◽  
Web Information ◽  
Web Information Systems ◽  
Definition Of

Recent years have seen the arrival of the Internet as the platform that supports most areas within organizations, a fact which has led to the appearance of specific methodologies and tools for the construction of Web information systems (WIS). However, an absence of functionalities for the verification and validation (V&V) has been detected in the methodologies and tools of the models which have been built. This chapter presents one of these methodologies for WIS development (MIDAS) and shows how it has been completed with the definition of a strategy for the formal specification of its models with V&V objectives. This will contribute to increasing the quality of the models used in WIS development. The plug-in architecture which integrates this formal approach within CASE tools for WIS development is also shown.

A Brief Introduction to Ontology

2009 ◽  
pp. 77-104
Author(s):  
Roberto Paiano ◽  
Anna Lisa Guido ◽  
Andrea Pandurino
Keyword(s):  
Information System ◽  
Information Systems ◽  
Initial Phase ◽  
Time Development ◽  
Development Effort ◽  
Web Information ◽  
Final Output ◽  
Web Information Systems ◽  
Final System

It is now clear that a careful initial phase of design, above all that it concerns for the complex Web information systems, it is essential to assure the quality of the final system. To reduce the necessary time development effort in order to get the final output, it is important to have tools that allow quickly obtatining tangible results; in few words, it is important to quickly obtain a consistent part of code for the final application. In this way, it is possible to provide the customer with a first draft of the information system in order to have a first validation of the design.

Enhanced Google-Based Semantic Category Search

2015 ◽  
Vol 1 (4) ◽  
pp. 398
Author(s):  
Mohammed Adeeb ◽  
Ahmed Sleman ◽  
Sumaya Abdullah ◽  
Belal Al-Khateeb
Keyword(s):  
Search Engines ◽  
Semantic Category ◽  
Search Method ◽  
Research Directions ◽  
The Social ◽  
Category Search

Recently search services have been developed rapidly especially when the social internet appeared. It can help web users easily find their documents. So that it is very difficult to find a best search method. This paper aims to enhance the quality of the search engines results and this can be done by adding a second level category search that is able to search for the keyword and its synonyms, which enables the search engines to get more users queries related results. The proposed method showed promising results that will open further research directions

Automatic Mining of Quantitative Association Rules with Gravitational Search Algorithm

2017 ◽  
Vol 27 (03) ◽  
pp. 343-372 ◽  
Author(s):  
Umit Can ◽  
Bilal Alatas
Keyword(s):  
Association Rules ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Fitness Function ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Search Space ◽  
Search Method ◽  
Quantitative Association Rules ◽  
Gravitational Search

The classical optimization algorithms are not efficient in solving complex search and optimization problems. Thus, some heuristic optimization algorithms have been proposed. In this paper, exploration of association rules within numerical databases with Gravitational Search Algorithm (GSA) has been firstly performed. GSA has been designed as search method for quantitative association rules from the databases which can be regarded as search space. Furthermore, determining the minimum values of confidence and support for every database which is a hard job has been eliminated by GSA. Apart from this, the fitness function used for GSA is very flexible. According to the interested problem, some parameters can be removed from or added to the fitness function. The range values of the attributes have been automatically adjusted during the time of mining of the rules. That is why there is not any requirements for the pre-processing of the data. Attributes interaction problem has also been eliminated with the designed GSA. GSA has been tested with four real databases and promising results have been obtained. GSA seems an effective search method for complex numerical sequential patterns mining, numerical classification rules mining, and clustering rules mining tasks of data mining.

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