Next-generation Search Engine Research Articles

DEVA a Methodology based on User-Centered Design for the development of a search system for judicial documents

Summary: This work provides a methodology to analyze user preferences regarding the components that a judicial search engine should include. We validate this methodology by developing a search system. Starting from initial characteristics, we designed a search prototype. A test was then applied to identify whether the search engine meets the user's needs. The prototype developed was compared to other next-generation search engines in terms of user satisfaction and accuracy. The results show that our proposal outperforms other search engines. Objective: Define and implement the components for the development of a judicial search engine. Methodology: The methodology consists of in: Definition: Includes a review of the state of the art of the technologies associated with the project. Prototype development: Different modules and components of the system are developed here. Evaluation: focused on usability and user satisfaction. Results: The characteristics and elements necessary for the search engine were identified. To this end, Benchmarking on general aspects and components of jurisprudence search engines was carried out. Additionally, a survey was conducted with 79 legal experts. Finally, a use test was carried out. Conclusions: A prototype of the search engine was designed according to the characteristics declared by the users. This prototype showed optimal usability and navigation because it was designed considering the needs of the user's jurisprudence. Its interfaces are easy to understand and its filters make the search process more agile and precise. Finally, the developed search engine offers a good experience to the users.

Structural Information and Dynamical Complexity of Networks

In 1953, Shannon proposed the question of quantification of structural information to analyze communication systems. The question has become one of the longest great challenges in information science and computer science. Here, we propose the first metric for structural information. Given a graph $G$ , we define the $K$ -dimensional structural information of $G$ (or structure entropy of $G$ ), denoted by $\mathcal {H}^{K}(G)$ , to be the minimum overall number of bits required to determine the $K$ -dimensional code of the node that is accessible from random walk in $G$ . The $K$ -dimensional structural information provides the principle for completely detecting the natural or true structure, which consists of the rules, regulations, and orders of the graphs, for fully distinguishing the order from disorder in structured noisy data, and for analyzing communication systems, solving the Shannon’s problem and opening up new directions. The $K$ -dimensional structural information is also the first metric of dynamical complexity of networks, measuring the complexity of interactions, communications, operations, and even evolution of networks. The metric satisfies a number of fundamental properties, including additivity, locality, robustness, local and incremental computability, and so on. We establish the fundamental theorems of the one- and two-dimensional structural information of networks, including both lower and upper bounds of the metrics of classic data structures, general graphs, the networks of models, and the networks of natural evolution. We propose algorithms to approximate the $K$ -dimensional structural information of graphs by finding the $K$ -dimensional structure of the graphs that minimizes the $K$ -dimensional structure entropy. We find that the $K$ -dimensional structure entropy minimization is the principle for detecting the natural or true structures in real-world networks. Consequently, our structural information provides the foundation for knowledge discovering from noisy data. We establish a black hole principle by using the two-dimensional structure information of graphs. We propose the natural rank of locally listing algorithms by the structure entropy minimization principle, providing the basis for a next-generation search engine.

Comparison of Research Speed and Accuracy Using WestlawNext and Lexis Advance

ABSTRACTIn 2010, Thomson Reuters released a new search engine to the legal academy called WestlawNext. WestlawNext's single-search-box approach revolutionized the legal research process. LexisNexis followed with its own next-generation search engine, Lexis Advance. This study compares the speed and accuracy of WestlawNext and Lexis Advance for basic legal research questions. Fifty-five participants answered five legal questions in each system. We reviewed their results and research trails to determine how the systems compared on speed and accuracy. Our results indicate few significant differences between the two systems for basic legal research tasks utilizing keyword searches.

Question Answering over Knowledge Bases

Question answering over knowledge bases is a challenging task for next-generation search engines. The core of this task is to understand the meaning of questions and translate them into structured language-based queries. Previous research has focused on a specific knowledge base with a constrained domain, but with the increase in the size and domain of existing knowledge bases, fulfilling this aim is even more challenging. This article introduces the mainstream methods for question answering over knowledge bases, describing typical semantic meaning representation models and state-of-the-art systems for converting questions to predefined logical forms. It also puts a particular focus on the approaches for question answering over a large-scale knowledge base and multiple heterogeneous knowledge bases.

A Query-by-Humming System based on Marsyas Framework and GPU Acceleration Algorithms

Query-by-humming(QBH) is a content-based music retrieval method and represents the trend of the next-generation search engine. Existing QBH systems still have the problems that most of the retrieval algorithms are of slower searching speeds than the traditional query-by-text ones; lacks a practical QBH system based on the Masyas framework and the GPU acceleration algorithms. This paper introduces a query-by-humming system which is based on the Marsyas framework and GPU acceleration algorithms. The system design, the humming retrieval process, the humming signal feature extraction, the melody libraries establishment and corresponding retrieval algorithms, the GPU parallel speed-up algorithms, and the experiments are presented in detail. The experimental results verify the functionality and good performance of the proposed methods by the speedup of more than 10X with our GPU acceleration algorithms.

Research on Safe and Reliable Architecture for Enhanced Search Engine base on RUP

In this paper, we conduct the risk assessment for the search engine workflow, complete the design of the corresponding safe and reliable module. With RUP “4 +1” view, from the different dimensions we describe the risk points and safe modules, culminating the safe and reliable architecture for the enhanced search engine, in order to provide the method of the safe and reliable technology for next-generation search engine.

Semantic Web – Interoperability, Usability, Applicability

While this statement seems obvious, this has not been so a few years ago, when basic research funding seemed to be running out, and industrial uptake was hardly happening. In the meantime, we do not only see sustained funding for Semantic Web related research (in particular by the European Commission), but also significant investment by industry, including major IT and venture capital companies. The Semantic Web is here to stay – and to grow. The Semantic Web is multidisciplinary and heterogeneous. Many Semantic Web researchers maintain close ties to neighboring disciplines which provide methods or application areas for their work. However, the Semantic Web has now established itself as a research field in its own rights. Consequently, a growing number of researchers, in particular those of the second or third generation, seem to identify themselves with the Semantic Web as their primary field of work. The growing number of top quality events dedicated to Semantic Web topics is also a clear indication of this trend. Another indicator is the increasing interweavement of Semantic Web methods into related disciplines leading to research topics such as geospatialsemantics, the Semantic Sensor Web, semantic desktop, or work on cultural heritage. The Semantic Web journal is set up to be a forum for highest-quality research contributions on all aspects of the Semantic Web. Its scope encompasses work in neighboring disciplines which is motivated by the Semantic Web vision. Besides the publishing of research contributions, it is also an outlet for reports on tools, systems, applications, and ontologies which enable research, rather than being direct research contributions.1 The journal also publishes top-quality surveys which serve as introductions to core topics of Semantic Web research. The journal’s subtitle – Interoperability, Usability, Applicability – reflects the wide scope of the journal, by putting an emphasis on enabling new technologies and methods. Interoperability refers to aspects such as the seamless integration of data from heterogeneous sources, on-the-fly composition and interoperation of Web services, and next-generation search engines. Usability encompasses new information retrieval paradigms, user interfaces and interaction, and visualization techniques, which in turn require methods for dealing with context dependency, personalization, trust, and provenance, amongst others, while hiding the underlying computational issues from the user. Applicability refers to the rapidly growing application areas of Semantic Web technologies and methods, to the issue of bringing state-of-the-art research results to bear on real-world applications, and to the development of new methods and foundations driven by real application needs from various domains.