Top PDF Economic growth and the design of search engines

Economic growth and the design of search engines

Economic growth and the design of search engines

This is done in the context of a "qualitative" growth model in which there are physical limits to the number of goods that can be produced (there is no physical productivity growth) and consumed (one can only consume 0 or 1 unit of each good), but goods differ in their quality and the introduction of new blueprints, by increasing the total number of available goods, allows consumers to select higher quality goods. If the distribution of quality lev- els is unbounded, horizontal innovation may lead to sustained qualitative growth. That assumption is meant to capture a modern feature of the "new economy": given that it is pointless to buy the same CD, videogame, etc, twice and given that there consuming these goods is time intensive, the only scope for growth is indeed an improvement in their quality. In the model, existing goods cannot raise their quality and growth is associated with "cre- ative destruction" in that at some point consumers stop buying a good as they switch to higher quality products.
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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

Current MAC design for wireless sensor networks can be broadly divided into contention-based and TDMA protocols. The standardized IEEE 802.11 distributed coordination function (DCF) [1] is an example of the contention-based protocol, and is mainly built on the research protocol MACAW [15]. It is widely used in ad hoc wireless networks because of its simplic- ity and robustness to the hidden terminal problem. But, re- cent work [2] has shown that the energy utilization using this MAC is very high when nodes are in idle mode. This is mainly due to the idle listening. PAMAS [10] made an improvement by trying to avoid the overhearings among neighboring nodes. Our paper also exploits similar method for energy savings. The main difference of our work with PAMAS is that we do not use any out-of-channel signaling. Whereas in PAMAS, it requires two independent radio channels, which in most cases indicates two independent radio systems on each node. PAMAS does not address the issue of reduce idle listening The other class of MAC protocols is based on scheduling and reservation, for example TDMA-based protocols. TDMA protocols are useful for energy conservation compared to contention protocols because the duty cycle of the radio is reduced and there is no contention-introduced overhead and collisions. But, TDMA protocol requires the nodes to form actual communication clusters, like Bluetooth [16], [17] and LEACH [13]. Managing inter cluster communication is not an easy task. Moreover, when the number of nodes within a cluster changes, it is not easy for a TDMA protocol to dynamically change its frame length and time slot assignment. So its scalability is generally not as good as that of a contention-based protocol. For example, Bluetooth may have at most 8 active nodes in a cluster.
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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

Information security means protecting information and systems from security threats such as unauthorized access, use, disclosure, disruption, modification or destruction of information. The frequency of information security breaches is growing and common among most organizations. Internet connection is increasingly cited as a frequent point of attack and likely sources of attacks are independent hackers and disgruntled employees. Despite the existence of firewalls and intrusion detection systems, network administrators must decide how to protect systems from malicious attacks and inadvertent cascading failures. Effective management of information security requires understanding the processes of discovery and exploitation used for attacking. An attack is the act of exploiting a vulnerability that is a weakness or a problem in software (a bug in the source code or flaw in design). Software exploits follow a few patterns; one example is buffer overflow. An attack pattern is defined as a “blueprint for creating a kind of attack” (Hoglund & McGraw, 2004, p. 26). Buffer overflow attacks follow several standard patterns, but they may differ in timing, resources used, techniques and so forth.
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Search Engines Going beyond Keyword Search: A Survey

Search Engines Going beyond Keyword Search: A Survey

Traditional keyword/text based search lacks understanding of the user’s intent and the web’s content both queries and documents are typically treated as a word, missing semantic-level under- standing. The solution of improving search accuracy is by un- derstanding searcher intent and the contextual meaning of terms. Dittenbach et al. [10] presents ConceptWorld, an instrument to automatically discover various facets of a topic of interest by extracting concepts from Web documents. The result material- izes as a network of semantic concepts with their various con- textual interrelations and provides a holistic view on the topic of interest. Liu et al. [19] introduced semantic web technologies to e-commerce search field, and designed a semantic network structure for the new search system, and discussed the key tech- nologies in e-commerce semantic search, such as semantic struc- ture and semantic search algorithm. Compared with traditional search, semantic search can return more relevant semantic infor- mation and can extract users’ search input more accurate. Zou et al. [36] propose and implement a semantic search prototype system. The experimental results show that semantic expansion search by proposed methodology can overcome limitations in comparison with traditional keyword search mode, and achieve higher recall ratio and precision ratio. Lee and Tsai [18] design an interactive semantic search engine which collects feedback by means of selection in order to better capture users personal con- cepts. Chiang et al. [7] present a semantic search engine based on the smart web query (SWQ) method for web data retrieval. The SWQ architecture contains three main parts: SWQ search engine and its subcomponents: ”query parser” and ”context ontology determination engine”; context ontologies for domains of appli- cation; a semantic search filter which is to improve search pre- cision based on retrieving term properties in context ontologies. Bhagwat and Polyzotis [3] propose a semantic-based file system search engine —Eureka, which uses an inference model to build the links between files and a FileRank metric to rank the files according to their semantic importance. Kandogan et al. [17] de- velop a semantic search engine Avatar, which combines the tra- ditional text search engine with use of ontology annotations [17]. Avatar has two main functions: (1) extraction and representation (2) interpretation a process of automatically transforming a key- word search to several precise searches.
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INTRODUCTION TO WEB SEARCH ENGINES

INTRODUCTION TO WEB SEARCH ENGINES

ABSTRACTA: web search engine is a program designed to help find information stored on the World Wide Web. Search engine indexes are similar, but vastly more complex that back of the book indexes. The quality of the indexes, and how the engines use the information they contain, is what makes or breaks the quality of search results. The vast majority of users navigate the Web via search engines. Yet searching can be the most frustrating activity using a browser. Type in a keyword or phrase, and we're likely to get thousands of responses, only a handful of which are close to what we looking for. And those are located on secondary search pages, only after a set of sponsored links or paid-for-position advertisements. Still, search engines have come a long way in the past few years. Although most of us will never want to become experts on web indexing, knowing even a little bit about how they're built and used can vastly improve our searching skills. This paper gives a brief introduction to the web search engines, architecture, the work process, challenges faced by search engines, discuss various searching strategies, and the recent technologies in the web mining field.
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Designing of MCAM Using 22nm Technology

Designing of MCAM Using 22nm Technology

ABSTRACT: The main objective of our project work deals with the design and analysis of high speed performance Memristor based content addressable memory for future search engines to develop low power consumption and no loss of store data in a cell even if the power supply is turn OFF. The ever-increasing demand for larger data storage capacity has driven the fabrication technology and memory development towards more compact design rules and, consequently, toward higher data storage densities.

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A Survey on Search Engines

A Survey on Search Engines

Web surfing for various purposes has become a habit of humans. Searching for information from the Internet today has been made easier by the widely available search engines. However, there are many search engines and their number is increasing. It is of considerable importance for the designer to develop quality search engines and for the users to select the most appropriate ones for their use. The Information quality linked through these searches is quite irregular. There are fair chances that the retrieved results are irreverent and belong to an unreliable source. In fact, most search engines are developed mainly for better technical performance and there could be a lack of quality attributes from the customers’ perspective. In this paper, we first provide a brief review of the most commonly used search engines, with the focus on existing comparative studies of the search engines. The paper also includes a survey conducted of 137 respondents where the identified user expectations will be of great help not only to the designers for improving the search engines, but also to the users for selecting suitable ones. The objective behind this study was also to find the reason behind poor precision and recall of so many available search engines. The study finally aims to enhance user search experience.
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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

Indian economy has shown an impressive growth of over 6 per cent for last five years and continues to surge ahead. GDP growth rate in 2003-04 recorded a fifteen year high of 8.5% and subsequently maintained a steady growth for the next two years. Real GDP growth accelerated from 7.5 per cent during 2004-05 to 8.4 per cent during 2005-06 on the back of buoyant manufacturing and services activity supported by a recovery in the agricultural sector. The central bank forecasts similar growth of 7.5-8 percent during 2006-07. With strong economic growth consumerism is increasing in the country and India is the fourth largest economy as far as purchasing power parity is concerned, just behind USA, Japan and China. (The Economic Times 27 june,2007) Retailing in India is receiving global recognition and attention and this emerging market is witnessing a significant change in its growth and investment pattern. It is not just the global players like Wal-Mart, Tesco and Metro group are eying to capture a pie of this market but also the domestic corporate players like Reliance, KK Modi, Aditya Birla group, and Bharti group too are also the runner in marathon of retail development. Reliance, announced that it will invest $3.4 billion to become the country's largest modern retailer by establishing a chain of 1,575 stores by March 2007. The last couple of years have been rosy for real estate developers and the retailers are finding suitable retail space in prominent locations. There is increased sophistication in the shopping pattern of consumers, consumer tastes and preferences are changing, radical alteration in life styles and strong surge in income which has resulted in big retail chain coming up in most metros, mini metros and towns being the next target. As a result the industry is buoyant about growth and the early starters are in the expansion mood. Companies need to be dynamic and proactive while responding to the ever-changing trends in consumer lifestyle and behavior.
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History Of Search Engines

History Of Search Engines

As the number of sites on the Web increased in the mid-to-late 90s, search engines started appearing to help people find information quickly. Search engines developed business models to finance their services, such as pay per click programs offered by Open Text in 1996 and then Goto.com in 1998. Goto.com later changed its name to Overture in 2001, and was purchased by Yahoo! in 2003, and now offers paid search opportunities for advertisers through Yahoo! Search Marketing. Google also began to offer advertisements on search results pages in 2000 through the Google Ad Words program. By 2007, pay-per-click programs proved to be primary money-makers for search engines. In a market dominated by Google, in 2009 Yahoo! and Microsoft announced the intention to forge an alliance. The Yahoo! & Microsoft Search Alliance eventually received approval from regulators in the US and Europe in February 2010. Search engine optimization consultants expanded their offerings to help businesses learn about and use the advertising opportunities offered by search engines, and new agencies focusing primarily upon marketing and advertising through search engines emerged. The term "Search Engine Marketing" was proposed by Danny Sullivan in 2001 to cover the spectrum of activities involved in performing SEO, managing paid listings at the search engines, submitting sites to directories, and developing online marketing strategies for businesses, organizations, and individuals. Some of the latest theoretical advances include Search Engine Marketing Management (SEMM). SEMM relates to activities including SEO but focuses on return on investment (ROI) management instead of relevant traffic building (as is the case of mainstream SEO). SEMM also integrates organic SEO, trying to achieve top ranking without using paid means of achieving top in search engines, and PayPerClick SEO. For example some of the attention is placed on the web page layout design and how content and information is displayed to the website visitor.
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GLOBALIZATION AND THE SEARCH FOR ECONOMIC GROWTH AND DEVELOPMENT IN NIGERIA

GLOBALIZATION AND THE SEARCH FOR ECONOMIC GROWTH AND DEVELOPMENT IN NIGERIA

Globalization as a concept is not a new phenomenon in the world economy. It promises benefits to the Nigerian economy but its practice and adoption will on the other hand expose the economy to greater or even higher levels of dependence on the developed countries because of the neglect and/or abandonment of the inward looking initiatives. Lack of preparedness and powers to control the excesses of globalization are responsible for the countless political, economic, social and cultural upheavals, which often result in the huge losses in properties and other unaccountable resources across developing countries in particular and the World in general. Globalization as a Western initiative is, however, designed to benefit the industrialized/developed countries the most through the creation of larger markets and the accumulation of greater wealth. On the other hand, the developing countries are in the process made more vulnerably to massive exploitation. Globalization as an economic phenomenon has come to stay, and whether we benefit from it or we are marginalized by it, we have no choice, but to learn how best to live with it as a country.
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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

Abstract— One aspect of Multiagent systems (MAS) that has been only partially studied is their role in software engineering and in particular their merit as a software architecture style.We studies a particular multiagent resource allocation problem with indivisible and sharable resources. The utility of an agent for using a bundle of resources is the difference between the valuations of that bundle of resources. The valuation and the delay can be agent-dependent. Currently, the great majority of agent-based systems consist of a single agent. However, as the technology matures and addresses increasingly complex applications, the need for systems that consist of multiple agents that communicate in a peer-to-peer fashion is becoming apparent. Central to the design and effective operation of such multiagent systems (MAS) are a core set of issues and research questions that have been studied over the years by the distributed AI community.
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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

Abstract - In Mobile Ad hoc network (MANETS), no fixed infrastructure is available. Mobile Ad-hoc Networks (MANETs) are future wireless networks consisting entirely of mobile nodes that communicate on-the-move without base stations. Nodes in these networks will both generate user and application traffic and carry out network control and routing protocols. Rapidly changing connectivity, network partitions, higher error rates, collision interference, and bandwidth and power constraints together pose new problems in network control—particularly in the design of higher level protocols such as routing and in implementing applications with Quality of Service requirements. The MANET routing protocols have mainly two classes: Proactive routing (or table-driven routing) protocols and Reactive routing (or on-demand routing) protocols. In this paper, we have analyzed Random based mobility models: Random Waypoint model using AODV and DSDV protocols in Network Simulator (NS 2.35). The performance comparison of MANET mobility models have been analyzed by varying number of nodes type of traffic (TCP) and maximum speed of nodes. The comparative conclusions are drawn on the basis of various performance metrics such as: Routing Overhead (packets), Packet Delivery Fraction (%), Normalized Routing Load, Average End-to-End Delay (milliseconds) and Packet Loss (%).
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INCORPORATING DEOXYRIBONUCLEIC ACID IN AES SCHEME FOR ENHANCING SECURITY AND 
PRIVACY PROTECTION

INCORPORATING DEOXYRIBONUCLEIC ACID IN AES SCHEME FOR ENHANCING SECURITY AND PRIVACY PROTECTION

GOODRELATIONS [19] is a web ontology for e- commerce, is the most powerful vocabulary for publishing all of the details of products and services in a way friendly to search engines, mobile applications, and browser extensions. By adding a bit of extra code to the Web content, it make sure that potential customers realize all the great features and services and the benefits of doing business with vendors, because their computers can extract and present this information with ease.

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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

In Table 1, the share A’ and share A” represent the results of share A rotated 90o clockwise and 90o counterclockwise, respectively, rotating the share A clockwise 90o and stacks it wi[r]

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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

• At Gram Panchayat level majority of Panches don’t feel free while at Panchyat Samiti level most of women and at Zila parishad level all the women feel free while interacting in PRI me[r]

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Defining Algorithmic Ideology: Using Ideology Critique to Scrutinize Corporate Search Engines

Defining Algorithmic Ideology: Using Ideology Critique to Scrutinize Corporate Search Engines

Turning to Gramsci’s notion of hegemony, in contrast, enables us to identify moments of struggle that open up the view for counter-activity and alternative futures. Röhle (2009) described Google’s strategy of convincing website providers and users to play by the rules as a clever system of “punishments and rewards”. Website providers who follow the rules get rewarded with a good “seat” in Google’s search results, while those who transgress the rules by using illicit SEO practices get punished with a lower search engine position (or even an exclusion from the index). Similarly, users who try to opt out of Google’s data collecting practices by changing default privacy settings, reconfiguring their web browsers, or turning off cookies are punished with less convenient services than cooperating users get. This shows how Google makes both website providers and users play by the rules. It further shows that Google’s hegemony is not fixed or stabilized, but that it is constantly negotiated and made. “As a concept, then, hegemony is inseparable from overtones of struggle” (Eagleton 1991, 115). This struggle has the potential to challenge powerful ac- tors like Google and their algorithmic ideology. If content providers and users broke out of the network dynamic, the power of Google and its whole business model would fall apart. If the media would feature more critical stories about Google’s data collecting practices, privacy violations and possible collaborations with secret services dissatisfaction and pro- test would significantly grow in the public domain; as we have seen in the past months. If politics and law took on a stronger role in the regulation of search technology, limits would be set regarding the collection and use of personal data, but also business practices and advertising schemes. In an age of neoliberal policy, however, governments have widely failed to tame corporate players like Google. Quite on the contrary, the politics of privatiza- tion has pushed search on the free market in the first place. This shows that new types of actors, “organic intellectuals” in the words of Gramsci (2012), are needed to challenge corporate players like Google and its ideology.
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Jigs and Lures: Associating Web Queries with Structured Entities

Jigs and Lures: Associating Web Queries with Structured Entities

100 queries. The former consists of 203 query- product associations, and the latter of 159 associa- tions. The evaluation was done using Amazon Me- chanical Turk 4 . We created a Mechanical Turk HIT 5 where we show to the Mechanical Turk workers the query and the actual Web page in a Product search engine. For each query-entity association, we gath- ered seven labels and considered an association to be correct if five Mechanical Turk workers gave a pos- itive label. An association was considered to be in- correct if at least five workers gave a negative label. Borderline cases where no label got five votes were discarded (14% of items were borderline for the uni- form sample; 11% for the weighted sample). To en- sure the quality of the results, we introduced 30% of incorrect associations as honeypots. We blocked workers who responded incorrectly on the honey- pots so that the precision on honeypots is 1. The result of the evaluation is that the precision of the as- sociations is 0.88 on the weighted sample and 0.90 on the uniform sample.
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ONTOLOGY BASED WEB SEARCH

ONTOLOGY BASED WEB SEARCH

The paper presents an approach for improving the web search result.Ontology similarity is unquestionable important for Semantic Web search engine.This paper tries to propose an ontology similarity basedapproach to measure similarity between the users query and web page. This paper makes an attempt to propose a solution for information retrieval to retrieve higher occurrence of the concepts, within the web pages dynamically, Which reduces the effort made by the user for searching the required concept, In which semantic
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11- Unit 10 ( Pages 995-1031).pdf

11- Unit 10 ( Pages 995-1031).pdf

Doing research means locating, analyzing, and understanding information in order to answer a question. You may already be skilled at tracking down some types of information, such as movie times and sports statistics. However, there are always new resources to find and ways to improve your search. In this unit, you will learn to find, use, and evaluate sources of information. You will also learn how to improve your ability to search for sources and judge the sources you already use.

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Ranking Techniques in Search Engines

Ranking Techniques in Search Engines

The web page ranking algorithms rank the search results depending upon their relevance to the search query. For this algorithms rank the search results in descending order of relevance to the query string being searched. A web page’s ranking for a specific query depends on factors like- its relevance to the words and concepts in the query, its overall link popularity etc. There are three categories of these algorithms viz. text based ranking, PageRank which is based on links and user based ranking.

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