Web Search Services Research Articles

Unveiling the Hidden Dynamics: exploring causative factors and impact of employee turnover on organisational performance.

Employee turnover is a widely recognised subject in an organisational setting. Although academics and organisational human resource departments have accepted the fact that employee turnover can have a disastrous impact on the organisation, there are limited studies conducted on the causative factors and effects of employee turnover in organisations. Therefore, this study helped to highlight some of the causative factors triggering employee turnover and their impact on an organisation. In addition, the study also suggests vital strategies for mitigating and reducing employee turnover. In line with the preceding assertion, the cross-sectional qualitative study taking into consideration conference papers, government periodicals, chronological documents, and mainly secondary and primary sources were used. Online search engines such as Scopus, EBSCO, Emerald, science direct, and unrestricted web service search engines such as google scholar and Mendeley demonstrated to be valuable database resources. The finding indicated that performance appraisal feedback, job insecurity, stress and work overload, death, and compensation are significant factors responsible for employee turnover was also deduced that employee turnover can affect organisational performance through ineffectuality in the delivery of service, increase in workload, errors in work processes and reduction in sense of loyalty. However, findings also postulated that training and development, competitive benefits and compensation, effective leadership, and job satisfaction are key procedures that help in reducing and mitigating employee turnover.

INFRASTRUCTURES OF MANIPULATION

This panel presents research on web and information infrastructures used for manipulative purposes. In contrast to platform manipulation (Woolley & Howard, 2018; Benkler et al., 2018), where users such as bad actors seek to gamify and exploit the weaknesses of online social media platforms like Twitter and TikTok, the papers in the present panel describe studies where web or information infrastructures such as those involved in search and information retrieval are manipulated to alter or produce facts (rather than social commentary on facts). For example, studies have shown how infrastructures like Google Search are manipulated by conservative elites (Tripodi, 2022), how anonymous editors use Wikidata to revise the distribution of information related to political protest movements (Ford, 2022), and how administrators harness information schemas to improve the findability of their advertising content (Iliadis, 2022). In these areas and more, web and digital infrastructures are being manipulated to serve the interests of politically motivated actors (Acker, 2018; Acker & Donovan, 2019). Infrastructures typically refer to shared public services like sewers, telephone poles, and electricity. According to Bowker et al. (2010, p. 98), information infrastructure refers to “digital facilities and services usually associated with the internet.” Information infrastructures are thus enabling resources, in network form, whose key role is that of a distributor, but rather than goods or services, information infrastructures distribute “knowledge, culture, and practice” (Bowker et al., 2010, p. 114). Such structures do this through their development of ontologies or classification schemes that enable dividing the world into categories or, through their application to large data sets, by offering an enormous, open store of data that can be used by others for a variety of purposes, such as retrieving facts and sharing information. Recently, several scholars have elaborated on the political nature of such infrastructural processes of digitization and datafication, including in the domains of archiving and preservation (Thylstrup, 2018, 2022), governance and management (Flyverbom & Murray, 2018), metrics and sorting (Alaimo & Kallinikos, 2021), and the creation of global ontologies for things like web search (Iliadis et al., 2023) and surveillance services (Iliadis & Acker, 2022). Manipulation of social media content and messaging is likewise a major research area over the last several years owing to the prevalence of online misinformation and disinformation campaigns (Reagle, 2016; Paris, 2021; Culloty & Suiter, 2021), particularly those associated with electoral politics (Tucker & Persily, 2020) and health misinformation (Keselman et al., 2022). Yet, online manipulation is not a new phenomenon and has long been discussed as a feature of the web in the context of the history of trolling, abuse, and hate (Phillips, 2015, 2019). Manipulation is thus a multivalent concept and is found in several domains which share the notion that manipulation is related to the altering, editing, treating, controlling, and influencing of content and messages for the purpose of misleading individuals. Historically, though, less attention has focused on manipulation as it has been mobilized infrastructurally, particularly with respect to the information infrastructures that transmit content and messages. Infrastructures should be understood here in a broad sense as undergirding the communication structures that transmit messages and content. Such infrastructures can be found in computer science, news and journalism, government, policy, and other areas where messaging is organized using some form of schema, whether it be technical, linguistic, financial, or otherwise. The first paper uses interviews to highlight the “importance of abortion-related web search and whether or not that system has been manipulated by actors trying to prevent abortion access.” The paper “examines how people (users) search for information about abortion, how organizations (content providers) utilize search engine optimization to reach potential users, and how advertisers try to attract visitors.” The second paper uses autoethnography and process tracing with respect to “the AP African American Studies debacle in order to elucidate digitally mediated disinformation as a strategy for stoking moral panic and thereby gaining widespread public buy-in to the establishment of educational censorship infrastructure.” The third paper analyzes Palantir as a surveillance platform that shapes and is shaped by infrastructures of manipulation. The paper “provides a method for researching companies like Palantir and its surveillance infrastructures” through digital media archiving of “over 600+ documents which have been stored, cleaned, annotated, and uploaded into an online digital archive that will be publicly available for media researchers to study.” The fourth and final paper is “an ethnographic study of a single Wikipedia article and how it evolved over the course of a decade” in the context of political revolutons. The paper describes “a framework for understanding new methods of controlling facts in the context of automated knowledge products” and “the importance of semantic infrastructure to new methods of control and influence on Wikipedia and the wider knowledge infrastructures that are increasingly dependent on it.”

Development of a Visual Search Service Effectiveness Scale for Assessing Image Search Effectiveness: A Behavioral and Technological Perspective

Despite the potential of visual search services (VSSs) to increase the size of the global visual search market, there is no VSS effectiveness measurement scale in the literature. Prior studies of traditional text-based search services have aimed to establish a method for assessing the performance of web search services. Our primary objective is to integrate state-of-the-art research in the fields of information-seeking behavior, visual search performance, and human–computer interaction pertaining to evaluating VSS effectiveness. The key dimensions of VSS effectiveness were identified by adopting the Delphi method, and the associated measures were developed. Then, survey data were collected from 426 VSS users, and the developed measures of VSS effectiveness were validated using the exploratory factor analysis technique. Finally, the scale developed includes 19 measures belonging to three key dimensions: user dependency on VSSs, the perceived ability to use VSSs, and VSS retrieval performance. The nomological validity of the developed scale’s three dimensions was also ensured and was evident from the positive correlations between them and VSS user continuance intention. Overall, we find that the better the functionality of a VSS is, the more users with a high perceived ability can acquire better information. This study also contributes to the theory development in the literature on search service effectiveness measures in terms of highlighting the VSS feature to be considered when providing a VSS that is suitable for the user’s preference.

AI co-pilot: content-based image retrieval for the reading of rare diseases in chest CT

The aim of the study was to evaluate the impact of the newly developed Similar patient search (SPS) Web Service, which supports reading complex lung diseases in computed tomography (CT), on the diagnostic accuracy of residents. SPS is an image-based search engine for pre-diagnosed cases along with related clinical reference content (https://eref.thieme.de). The reference database was constructed using 13,658 annotated regions of interest (ROIs) from 621 patients, comprising 69 lung diseases. For validation, 50 CT scans were evaluated by five radiology residents without SPS, and three months later with SPS. The residents could give a maximum of three diagnoses per case. A maximum of 3 points was achieved if the correct diagnosis without any additional diagnoses was provided. The residents achieved an average score of 17.6 ± 5.0 points without SPS. By using SPS, the residents increased their score by 81.8% to 32.0 ± 9.5 points. The improvement of the score per case was highly significant (p = 0.0001). The residents required an average of 205.9 ± 350.6 s per case (21.9% increase) when SPS was used. However, in the second half of the cases, after the residents became more familiar with SPS, this increase dropped to 7%. Residents’ average score in reading complex chest CT scans improved by 81.8% when the AI-driven SPS with integrated clinical reference content was used. The increase in time per case due to the use of the SPS was minimal.

A survey of semantic web (Web 3.0), its applications, challenges, future and its relation with Internet of things (IoT)

The Semantic Web (Web 3.0) is an advancement of the existing web in which knowledge is given well-defined importance, allowing people and machines to operate better. The Semantic Web is the next step in the evolution of the Web. The semantic web improves online technologies in need of generating, distributing, and linking material. In literature, multiple surveys have been done on the semantic web (Web 3.0), but those surveys are limited to some specific topics. According to the best of our understanding, none of the surveys provides a comprehensive study about the applications, challenges, and future of the semantic web along with its relationship with the Internet of things (IoT). The previous surveys focused on the Web 3.0 without touching on applications or challenges or focused on only the application prospect of the web 3.0, focused on the just the challenges, or focused on web 3.0 relationship with either internet of things or knowledge graphs but failed to touch the other important factors i.e., failed to provide comprehensive web 3.0 survey. This survey paper covers the gaps created from the previous survey papers in the same field and provides a comprehensive survey about web 3.0, a comparison between web 1.0, 2.0, and 3.0, the study of application and challenges in web 3.0, the relationship between web 3.0 with IoT and knowledge graph. Moreover, it focuses on the evolution of the web, and semantic web along with an explanation of the various layers, ontology tools, and semantic web tools with their comparison and semantic web service search. Despite all the shortcomings and challenges, the semantic web is moving in the right direction, and it is the future of the web.

Tradeoff Options for Bipartite Graph Partitioning

Web connectivity graphs and similar linked data such as inverted indexes are important components of the information access systems provided by social media and web search services. The Bipartite Graph Partitioning mechanism of Dhulipala et al. [KDD 2016] relabels the vertices of large sparse graphs, seeking to enhance compressibility and thus reduce the storage space occupied by these costly structures. Here we develop a range of algorithmic and heuristic refinements to Bipartite Graph Partitioning (BP) that lead to faster computation of space-reducing vertex orderings whilst continuing to apply the same broad algorithmic paradigm. Using a range of web graph and information retrieval system index data as test cases, we demonstrate an implementation that executes up to approximately four times faster than the baseline implementation we commenced with, while holding compressibility approximately constant. We have also improved the asymptotic execution time of BP by replacing a sorting step by a customized median-finding step.

Comprehensive Review and Future Research Directions on Dynamic Faceted Search

In modern society, the increasing number of web search operations on various search engines has become ubiquitous due to the significant number of results presented to the users and the incompetent result-ranking mechanism in some domains, such as medical, law, and academia. As a result, the user is overwhelmed with a large number of misranked or uncategorized search results. One of the most promising technologies to reduce the number of results and provide desirable information to the users is dynamic faceted filters. Therefore, this paper extensively reviews related research articles published in IEEE Xplore, Web of Science, and the ACM digital library. As a result, a total of 170 related research papers were considered and organized into five categories. The main contribution of this paper is to provide a detailed analysis of the faceted search’s fundamental attributes, as well as to demonstrate the motivation from the usage, concerns, challenges, and recommendations to enhance the use of the faceted approach among web search service providers.

Hunger games search: Visions, conception, implementation, deep analysis, perspectives, and towards performance shifts

A recent set of overused population-based methods have been published in recent years. Despite their popularity, most of them have uncertain, immature performance, partially done verifications, similar overused metaphors, similar immature exploration and exploitation components and operations, and an insecure tradeoff between exploration and exploitation trends in most of the new real-world cases. Therefore, all users need to extensively modify and adjust their operations based on main evolutionary methods to reach faster convergence, more stable balance, and high-quality results. To move the optimization community one step ahead toward more focus on performance rather than change of metaphor, a general-purpose population-based optimization technique called Hunger Games Search (HGS) is proposed in this research with a simple structure, special stability features and very competitive performance to realize the solutions of both constrained and unconstrained problems more effectively. The proposed HGS is designed according to the hunger-driven activities and behavioural choice of animals. This dynamic, fitness-wise search method follows a simple concept of “Hunger” as the most crucial homeostatic motivation and reason for behaviours, decisions, and actions in the life of all animals to make the process of optimization more understandable and consistent for new users and decision-makers. The Hunger Games Search incorporates the concept of hunger into the feature process; in other words, an adaptive weight based on the concept of hunger is designed and employed to simulate the effect of hunger on each search step. It follows the computationally logical rules (games) utilized by almost all animals and these rival activities and games are often adaptive evolutionary by securing higher chances of survival and food acquisition. This method's main feature is its dynamic nature, simple structure, and high performance in terms of convergence and acceptable quality of solutions, proving to be more efficient than the current optimization methods. The effectiveness of HGS was verified by comparing HGS with a comprehensive set of popular and advanced algorithms on 23 well-known optimization functions and the IEEE CEC 2014 benchmark test suite. Also, the HGS was applied to several engineering problems to demonstrate its applicability. The results validate the effectiveness of the proposed optimizer compared to popular essential optimizers, several advanced variants of the existing methods, and several CEC winners and powerful differential evolution (DE)-based methods abbreviated as LSHADE, SPS_L_SHADE_EIG, LSHADE_cnEpSi, SHADE, SADE, MPEDE, and JDE methods in handling many single-objective problems. We designed this open-source population-based method to be a standard tool for optimization in different areas of artificial intelligence and machine learning with several new exploratory and exploitative features, high performance, and high optimization capacity. The method is very flexible and scalable to be extended to fit more form of optimization cases in both structural aspects and application sides. This paper's source codes, supplementary files, Latex and office source files, sources of plots, a brief version and pseudocode, and an open-source software toolkit for solving optimization problems with Hunger Games Search and online web service for any question, feedback, suggestion, and idea on HGS algorithm will be available to the public at https://aliasgharheidari.com/HGS.html.

Study on Implementing Topic Maps-Based Web Search Services in Junior High School Library of Wugu

Web services have become well known in the school library, yet adoption of them with in the school setting still little have been down, especial in junior high school library. In this paper, we develop a Grade 1-9 Curriculum Web resources search services by using Web services, Grade 1-9 Curriculum, Topic Maps, XTM and relational database management system (RDBMS). The Grade 1-9 Curriculum was transferred into a Topic Maps to representation domain-specific knowledge model and to connect to related resources. This domain-specific knowledge of a topic is exploited by the Web search services to suggest appropriate search queries and retrieval adequate information from the internet. Finally, these functions are integrated into the WUGU junior high school library system and provide an efficient way for users to access heterogeneous information.

Appropriative practices and the ontology of economic form

Apesar de suas diferenças, tanto a economia tradicional quanto a economia política Marxista veem a economia contemporânea como um sistema de mercado completamente capitalista. Isso se traduz tanto na desconsideração de grandes áreas da economia, quanto no ocultamento da presença generalizada de outras formas econômicas. Esta situação se tornou mais significante e mais óbvia com a profusão de novos formatos econômicos na crescente economia digital, inclusive de tipos de dádivas e híbridos de dádiva e mercadoria. Em resposta, este trabalho propõe uma nova estrutura para analisar os diversos sistemas econômicos: uma ontologia das formas econômicas, na qual cada tipo é um complexo de práticas apropriativas. Diferentes formatos econômicos são estruturados por diferentes combinações de práticas e, podemos explicar como cada tipo opera pela análise das práticas envolvidas, e as tendências geradas por sua interação. Este argumento é demonstrado pela aplicação rápida a alguns exemplos da economia digital contemporânea: os serviços de busca da Wikipedia, Apple e Google. Este trabalho também deve ser lido como uma aplicação do realismo crítico a um caso empírico e, portanto, como um exemplo de algumas questões que surgem quando tentamos aplicar a abordagem realista na pesquisa social.

Reflective approach to improve self-adaptation of Web service compositions with autonomic middleware

Purpose This paper aims to propose an approach for the self-adaptation of the Web composition called SAMIWA. The SAMIWA framework helps users during the search, invocation and composition of the appropriate Web service. Design/methodology/approach The authors’ approach allows expressing requirements by taking into account potential users’ context in addition to the functional one. Findings In this paper, the authors introduce a new context-aware approach that provides a dynamic adaptation of service compositions. Originality/value The author has implemented a Web application that enables selection and composition of the most appropriate composite service.

Reduction of Search Space in Restful Service Discovery

Web Services has been enabled IT services and computing technology to perform business services more efficiently and effectively. REpresentational State Transfer (REST) is to be used for creating Web APIs/services. In the existing system, web service search engines for RESTful Web Services/Api’s provide Keyword, Tag and Semantic based search functions. One of the RESTful service discovery, referred as Test-oriented RESTful service discovery with Semantic Interface Compatibility (TASSIC) have been developed by the search of RESTful Service’s/Api’s. TASSIC approach will search the semantic characteristics of search and match interface terms in the service document. An inability to consider the classification and in finding the suitable Api’s or services are a key issue of the search space in Tassic. A new approach has proposed for reduction of the search space in restful service discovery to develop a k-Nearest Neighbor classification algorithm. it provide candidate services with ranking based on semantic similarity, and classifying of similar candidate services and service unit testing will be considered. This approach is meant for increasing search precision in the retrieval and quick search for classifying their RESTful services or Api according to user-defined criteria.

A Web service search engine for large-scale Web service discovery based on the probabilistic topic modeling and clustering

With the ever increasing number of Web services, discovering an appropriate Web service requested by users has become a vital yet challenging task. We need a scalable and efficient search engine to deal with the large volume of Web services. The aim of this approach is to provide an efficient search engine that can retrieve the most relevant Web services in a short time. The proposed Web service search engine (WSSE) is based on the probabilistic topic modeling and clustering techniques that are integrated to support each other by discovering the semantic meaning of Web services and reducing the search space. The latent Dirichlet allocation (LDA) is used to extract topics from Web service descriptions. These topics are used to group similar Web services together. Each Web service description is represented as a topic vector, so the topic model is an efficient technique to reduce the dimensionality of word vectors and to discover the semantic meaning that is hidden in Web service descriptions. Also, the Web service description is represented as a word vector to address the drawbacks of the keyword-based search system. The accuracy of the proposed WSSE is compared with the keyword-based search system. Also, the precision and recall metrics are used to evaluate the performance of the proposed approach and the keyword-based search system. The results show that the proposed WSSE based on LDA and clustering outperforms the keyword-based search system.

Learning to answer programming questions with software documentation through social context embedding

Official software documentation provides a comprehensive overview of software usages, but not on specific programming tasks or use cases. Often there is a mismatch between the documentation and a question on a specific programming task because of different wordings. We observe from Stack Overflow that the best answers to programmers’ questions often contain links to formal documentation. In this paper, we propose a novel deep-learning-to-answer framework, named QDLinker, for answering programming questions with software documentation. QDLinker learns from the large volume of discussions in community-based question answering site to bridge the semantic gap between programmers’ questions and software documentation. Specifically, QDLinker learns question-documentation semantic representation from these question answering discussions with a four-layer neural network, and incorporates semantic and content features into a learning-to-rank schema. Our approach does not require manual feature engineering or external resources to infer the degree of relevance between a question and documentation. Through extensive experiments, results show that QDLinker effectively answers programming questions with direct links to software documentation. QDLinker significantly outperforms the baselines based on traditional retrieval models and Web search services dedicated for software documentation retrieval. The user study shows that QDLinker effectively bridges the semantic gap between the intent of a programming question and the content of software documentation.

Compact inverted index storage using general‐purpose compression libraries

SummaryEfficient storage of large inverted indexes is one of the key technologies that support current web search services. Here we re‐examine mechanisms for representing document‐level inverted indexes and within‐document term frequencies, including comparing specialized methods developed for this task against recent fast implementations of general‐purpose adaptive compression techniques. Experiments with the Gov2‐URL collection and a large collection of crawled news stories show that standard compression libraries can provide compression effectiveness as good as or better than previous methods, with decoding rates only moderately slower than reference implementations of those tailored approaches. This surprising outcome means that high‐performance index compression can be achieved without requiring the use of specialized implementations.

Living in the Filter Bubble: Is What We Lose Something We Need to Preserve?

This paper examines the negative consequences of the filter bubble phenomenon, described by Eli Pariser in his book “The Filter Bubble. What the Internet Is Hiding from You” – the limitation of access to certain information due to the excessive and constant personalization of the content on web. The focus is given to the special role the search engines like Google, Yahoo or Bing play in the creation of filter bubble. The general aim of this paper is to raise awareness about the drawback of the current situation, to highlight possible threats posed to the deliberative democracy and briefly examine the possible solutions. Although it is arguable, the problem we might be facing with the personalization of Web and search results is that it poses a number of threats to the democratic society as well as to the values embodied in it e.g. freedom of speech, access to information or pluralism of opinions. The first chapter examines the filter bubble phenomenon in the context of how search engines contribute and might contribute to its existence. In this author’s view, although the search engines are just one of the personalized services creating the filter bubble, because of the role they play as actual information intermediaries in the information-based society, they are one of the most important factors in creation or destruction of the filter bubble. The part of the present paper discusses this interplay between search engines and information cocoons in which Living in The Filter Bubble we apparently live. The second chapter examines the threats posed by the filter bubble and so thus by the personalized Web search services. Following Sunstein’s thought, this paper assumes that the requirement of the deliberative democracy is not only that citizens have freedom of speech and the right to pluralism of thoughts, but that they are effectively exposed to other’s views and opinions. Being close in the filter bubble does not allow that to the significant degree, therefore it is possible that although the search engines do not block access to certain information, but somehow ‘hide’ it from users, that might be sufficient to pose a threat to the effective functioning of the exchange of opinions and thought, so thus to the deliberative democracy in general. Should then this issue be regulated? How? This issue is discussed in the final chapter of the paper, which suggest, that while the legal regulation is possible and needed, the field where the changes could happen now more easily and likely are social norms on the use of search engines. On the one hand, as to the principle, the public enjoys personalized content of the Web, as well as enhanced search results which it finds more accurate and helpful (individual interest). On the other hand, as indicated previously, the public interest might be endangered. Any discussion on possible regulation needs to acknowledge two opposite points of view. Therefore, the question of regulation remains not easily solvable. Following Lessig’s Code, the author examines whether the solution to the identified problem might be found through the change of architecture, social norms, and law or by the market forces. At the end of the day, the author suggests that the issue of the filter bubble and search engines appear to be a moral question on civil responsibility and therefore the first response to it could be found in the proper shaping of social norms. The ultimate response to the phenomenon of the filter bubble depends from the choice of values to be made by the members of society – little comfort or small act of social responsibility in pursue of protection of democratic values? Individualism over collectivism.

Spatial identity (re)constructed from web-sourced imagery

PurposeSpatial identity is an important constituent of general cultural identity in that it provides its share of continuity, sustainability, character and inertia. The purpose of this paper is to trace spatial identity’s formulation, reflection and perception within the mainstream media. The authors are particularly interested in spatial identity’s general aspect, consisting of architectural and other elements that give spatial character to places, making them both common and recognisable at the same time. The proposed spatial identity presence index is one of the indicators through which stakeholders in cultural heritage management could monitor, and even manage, the public perception of built heritage’s wider context.Design/methodology/approachThe research seeks wider relevance through the development of new methodology that combines web search services, visual data quantification, and data mining methods, and compares this with expert opinion. The research methodology is showcased and established in terms of the connection between the fundamental work in relation to Slovenian architectural landscapes from the pre-internet era and spatial identity’s web reflection as broadcast and collectively co-shaped by the internet-permeated society more than 20 years after the internet’s inception.FindingsThe findings indicate that results based on expert opinion and results acquired by counting spatial character carrier elements are aligned.Originality/valueThe introduced index of web-sourced spatial identity presence measures web-projected spatial characteristics in selected settlements. It is applicable in similar cases where the existing body of work on local spatial identity allows it, and can be used for comparative purposes. It also has social, economic and political connotations.

A study on web services discovery system based on the internetof things user information

IoT is a technology that provides service and shares information through connecting real objects through wireless and wired networks. Various services and information divided through IoT based environment device cooperation not only increases the quality of life in individuals but also has become an important issue in the development of various industrial fields. IoT service development appropriate for applicable industries and personal requirements is required. This study suggests a system that can provide a web service list appropriate for the user when selecting service by using a concept of applying and collecting various forms of information created in IoT environment while using web service. The suggested method applies user IoT information with traditional web service search to include the advantages of the existing search methods and services that the user needs. Thus, user friendly service selection that can increase the efficiency of service use is created compared with the traditional provider centered service provision environment. The study defines usable service properties and derives IoT service components. Based on this, we suggest an IoT information based web service search system and algorithm. Diverse user information models collected and created through IoT collector are provided with user requirements during service selection and based on user IoT information, useful service for individual user environment can be discovered and provided. The suggested method utilizes information models created through IoT device elements to suggest a system model that can be utilized for various requirements and rapidly changing services.

Cross-Lingual Topic Discovery From Multilingual Search Engine Query Log

Today, major commercial search engines are operating in a multinational fashion to provide web search services for millions of users who compose search queries by different languages. Hence, the search engine query log, which serves as the backbone of many search engine applications, records millions of users’ search history in a wide spectrum of human languages and demonstrates a strong multilingual phenomenon. However, with its salience, the multilingual nature of a search engine query log is usually ignored by existing works, which usually consider query log entries of different languages as being orthogonal and independent. This kind of oversimplified assumption heavily distorts the underlying structure of web search data. In this article, we pioneer in recognition of the multilingual nature of a query log and make the first attempt to cross the language barrier in query logs. We propose a novel model named Cross-Lingual Query Log Topic Model (CL-QLTM) to analyze query logs from a cross-lingual perspective and derive the latent topics of web search data. The CL-QLTM comprehensively integrates web search data in different languages by collectively utilizing cross-lingual dictionaries, as well as the co-occurrence relations in the query log. In order to relieve the efficiency bottleneck of applying the CL-QLTM on voluminous query logs, we propose an efficient parameter inference algorithm based on the MapReduce computing paradigm. Both qualitative and quantitative experimental results show that the CL-QLTM is able to effectively derive cross-lingual topics from multilingual query logs and spawn a wide spectrum of new search engine applications.

Enhancing service discovery using cat swarm optimisation based web service clustering

Summary Web service discovery is a critical task in service oriented application development. Due to extensive proliferation in the number of available services, it is challenging to obtain all the relevant services available for a given task. For the retrieval of most relevant Web services, a user would have to use those service-specific terms that best describe and match the natural language documentation contained within a service description. This process can be time intensive, due to functional diversity of available services in a repository. Domain specific clustering of Web Services based on the similarities of their functionalities would greatly boost the ability of a Web service search engine to retrieve the most relevant service. In this paper, we propose a novel technique to cluster service documents into functionally similar service groups using the Cat Swarm Optimisation Algorithm. We present experimental results that show that the proposed technique was effective and enhanced the process of service discovery.