A framework for hierarchical clustering based indexing in search engines

2010 ◽  
Author(s):  
Parul Gupta ◽  
A.K. Sharma
Keyword(s):  
Hierarchical Clustering ◽  
Search Engines

Handling WSD using Hierarchical Clustering Algorithm with sentences

2018 ◽  
pp. 83-88
Author(s):  
Mohana Priya K ◽  
Pooja Ragavi S ◽  
Krishna Priya G
Keyword(s):  
Hierarchical Clustering ◽  
Similarity Measure ◽  
Clustering Algorithm ◽  
Clustering Algorithms ◽  
Cosine Similarity Measure ◽  
Hierarchical Clustering Algorithm ◽  
Multiple Levels ◽  
Pos Tagger ◽  
Sentence Clustering ◽  
The Right

Clustering is the process of grouping objects into subsets that have meaning in the context of a particular problem. It does not rely on predefined classes. It is referred to as an unsupervised learning method because no information is provided about the "right answer" for any of the objects. Many clustering algorithms have been proposed and are used based on different applications. Sentence clustering is one of best clustering technique. Hierarchical Clustering Algorithm is applied for multiple levels for accuracy. For tagging purpose POS tagger, porter stemmer is used. WordNet dictionary is utilized for determining the similarity by invoking the Jiang Conrath and Cosine similarity measure. Grouping is performed with respect to the highest similarity measure value with a mean threshold. This paper incorporates many parameters for finding similarity between words. In order to identify the disambiguated words, the sense identification is performed for the adjectives and comparison is performed. semcor and machine learning datasets are employed. On comparing with previous results for WSD, our work has improvised a lot which gives a percentage of 91.2%

Classification of means and methods of the Web semantic retrieval

2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  
Keyword(s):  
Search Engines ◽  
Domain Knowledge ◽  
Information Needs ◽  
Web Search ◽  
User Interaction ◽  
Query Languages ◽  
Semantic Search ◽  
Semantic Retrieval ◽  
The Web

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.

Optimasi Blog Dengan Meta Tag Untuk Seo Dan Monitoringnya

2017 ◽  
Vol 15 (1) ◽  
pp. 45
Author(s):  
Valian Yoga Pudya Ardhana ◽  
Ahmad Wilda Yulianto
Keyword(s):  
Search Engines ◽  
The Elderly ◽  
Monitoring Process ◽  
Main Target ◽  
The Media

Blog as one of the media applicationson the Internethas been used all aroundIndonesia. The user wasnot limited  by age,ranging from children to the elderly. A lot of people notrealize that blogs can beoptimizedso thatthe bloggettingtoppositionsin search engines. Metatagwasone ofoptimization techniquesinSearch Engine Optimization (SEO).The main target washow to increaseblogtraffi requests. Afteroptimization, the next stepwasmonitoring, whichaims to determinethe extent to whichthe success ofoptimizationhas been done onSEO.The resultwas ablog sitegettingtoppositionsinthe search enginesandthe monitoring process resultsindicatethat thetitleand content was veryappropriatethat was 100%, description and contentwere alsoappropriatethat was 91%.

Peculiarities of the course of type I allergic reactions in patients with blood diseases

2020 ◽  
pp. 40-50
Author(s):  
A. Nikitina
Keyword(s):  
Search Engines ◽  
Anaphylactic Shock ◽  
Type I ◽  
Allergic Reactions ◽  
Common Cause ◽  
Blood Diseases ◽  
Treatment Regimens ◽  
Modern Methods

Analysis of literature data presented in search engines — Elibrary, PubMed, Cochrane — concerning the risk of developing type I allergic reactions in patients with blood diseases is presented. It is shown that the most common cause of type I allergic reactions is drugs included in the treatment regimens of this category of patients. The article presents statistics on the increase in the number of drug allergies leading to cases of anaphylactic shock in patients with blood diseases. Modern methods for the diagnosis of type I allergic reactions in vivo and in vitro are considered.

ROPO Effect in Gender- Generational Characteristics

2020 ◽  
Vol 11 (1) ◽  
pp. 43-43
Author(s):  
Radovan Bačík ◽  
Mária Oleárová ◽  
Martin Rigelský
Keyword(s):  
Association Analysis ◽  
Search Engines ◽  
Product Information ◽  
Customer Behavior ◽  
Internet Research ◽  
The Internet ◽  
Significant Progress ◽  
Customer Reviews ◽  
Online Purchase ◽  
Brick And Mortar

The development of the Internet and the current technologies have contributed to a significant progress in the consumer shopping process. Today, shopping decisions are more intuitive and much easier to make. E-shops, search engines, customer reviews and other similar tools reduce costs of searching for products or product information, thus boosting the habit of searching for information on the Internet - "Research Shopper Phenomenon" (Verhoef et al. 2007). According to Verhoef et al. (2015), this phenomenon leads to a phenomenon where consumers search for product information using one channel (Internet) and then make a purchase through another channel (brick-and-mortar shop). Heinrich and Thalmair (2013) refer to this effect as the "research online, purchase offline" or "ROPO" effect for short. This phenomenon can also be observed in reverse. Keywords: customer behavior, research online – purchase offline, association analysis

IMAGE THRESHOLDING BASED ON HIERARCHICAL CLUSTERING ANALYSIS AND PERCENTILE METHOD FOR TUNA IMAGE SEGMENTATION

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Alifia Puspaningrum ◽  
Nahya Nur ◽  
Ozzy Secio Riza ◽  
Agus Zainal Arifin
Keyword(s):  
Image Segmentation ◽  
Hierarchical Clustering ◽  
Gabor Filter ◽  
Hierarchical Cluster ◽  
Experimental Result ◽  
Main Process ◽  
Percentile Method ◽  
Cluster Analysis Method ◽  
2D Gabor Filter

Automatic classification of tuna image needs a good segmentation as a main process. Tuna image is taken with textural background and the tuna’s shadow behind the object. This paper proposed a new weighted thresholding method for tuna image segmentation which adapts hierarchical clustering analysisand percentile method. The proposed method considering all part of the image and the several part of the image. It will be used to estimate the object which the proportion has been known. To detect the edge of tuna images, 2D Gabor filter has been implemented to the image. The result image then threshold which the value has been calculated by using HCA and percentile method. The mathematical morphologies are applied into threshold image. In the experimental result, the proposed method can improve the accuracy value up to 20.04%, sensitivity value up to 29.94%, and specificity value up to 17,23% compared to HCA. The result shows that the proposed method cansegment tuna images well and more accurate than hierarchical cluster analysis method.

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