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Student Contributions March 9, 2012

Posted by Marquette MS Computing in Summer 2011 1st Session.
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These comments on the semantic web were created by students in the Professional Seminar,  an integral part of the Master of Science in Computing program at Marquette University. In this seminar students analyze technical and professional writings  on current topics and publish their opinions. Visit marquette.edu/computing to find out more about the program.

Why Semantic Web Technology Will Have a Major Impact on eCommerce and Search Engine Marketing July 5, 2011

Posted by tedtrisco in Summer 2011 1st Session.
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Taxonomy and classification is a large enough effort to begin with when constructing an online catalog. The eCommerce manager not only has to take into account the information architecture as it relates to the offline catalog or basic product offering structure, but also understand how online customers will navigate through the catalog when searching the store. If this organization isn’t done properly, it could mean the different between conversion and a customer visit bounce. Organizing product categories and products themselves seems intuitive enough to fit a semantic model. You have the category entities and parent-child relationships. Products sit on the branches of that category tree and products themselves have various attributes and relationships to fall within the eCommerce semantic web model. Taking a step back, however, to start with the customer in mind, will show us why the semantic web technology will have (and has?) a major impact on eCommerce and online marketing.

When using the web to shop online, users may start in a variety of places, one of those being search engines. With this in mind, a large effort of eCommerce deployment is structuring and classifying the pages on the eCommerce site for ease of search engine crawling and indexing. The focus primarily is to create a uniform and clean, yet keyword-rich, site to show to search engines that this page is relevant to the user searching for it’s content. eCommerce sites that do this well will see higher conversion rates, highlighting the fact that users who visit will purchase, as opposed to bouncing from the site back to results. To quickly digress, this is especially more important recently as Google announced an update to it’s Panda algorithm. Not only does inbound linking, keyword-rich content and correct SEO structure determine relevancy, but also now other non-traditional variables like “time on site” , numbers of returning users and  “non-natural language” quality factor in to the equation. But, a different topic for another day perhaps..

Now as Google and other search engines begin to use micro formats and RDF as part of the semantic web initiative, eCommerce managers have an additional item on their checklist to structure their store. When searching Google for business listings, products or other eCommerce entities, some result will populate visually different than others. For example, product listings will populate as shopping results, businesses will have contact information and ratings. While the shopping results are also populated from shopping feeds, these could and probably will be populated directly from eCommerce sites in the future, as the semantic web will allow search engines to crawl sites looking for classes like “product” and “product-image” or “product-price.” As this becomes the standard, the ability to offer up search results with more natural language  strings, as opposed to traditional keyword queries. For example, searching for “red shirt” and forcing the user to sift through the results and eCommerce site filters shifts to a search string of “red shirt XL under 15 dollars in milwaukee” is possible with the semantic web model. It’s easy to see the benefit from the consumer side and why an eCommerce store owner aiming for high conversion rates would buy-in to the model.

Why Semantic Technology Will Have a Major Impact on ‘Online’Shopping. July 4, 2011

Posted by mohammedsaati in Summer 2011 1st Session.
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Semantic Technology is the technology of what is related to meaning in language or logic. Starting from this logic in a structured organization, what does that mean to us?

It means the elimination of the need of change and re-writing the data to accommodate other meanings by just applying layers of relationships that point out to that meaning.

By that, we conserve manpower, cost and time that we need for re-writes and relating.

Most tools on the market nowadays are black boxes. You don’t know how they operate and cannot modify them. Developers need semantic tools that give you a fast start and preserve the flexibility to generate answers as unique as the market demands.

Using Semantic Technology in online shopping or shopping in general well definitely have a positive and enhanced experience to both vendors and shoppers. For a shopper, who for example is looking for a new laptop and thinking about it. What kind of model do I want? What processor power is good and enough?

These are simple questions that users might think about. Before, we had to go and check every vendor’s website and note down their prices and configuration. Now, it only needs the easy search of semantic words of what his/her needs are. For example alternative to searching each vendor’s website, we can search Google for “good laptop 500 – 1000 dollars”, and all companies well be competing to show results that they think you are asking for. Which are what we exactly searched for.

Not only that, going from there we can link all data to find and compare other products that are related to the first search to begin with.

Why semantic technology will have major impact on data of financial institutions July 1, 2011

Posted by sayemmarquette in Summer 2011 1st Session.
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The critical components of semantic web technology

According to my opinion,critical components  of semantic web technology are in the information parsing.The process is already there.The work of the parsing tool is to process the data and making it readable for the machine. Information are gathered from different sources.There are different types of data some are relevant and some are not relevant then some are structured and some are not structured,it can deal with all types data and parse it and makes it machine readable.It can make the data transferable from one machine to another machine.

Impact on financial data of financial institutions

The financial institutes can use this semantic technology and if they use this technology they can make their work more flexible.In the financial institutions there is lots of work dealing with money and also the financial institutions deals with a large range of matters, including bank and commercial lending, secured and unsecured lending, asset-based lending, leasing, project finance, structured finance, asset securitization, debt and equity securities offerings, trust services and regulatory counseling and representation before federal and state agencies. Dealing these types of matters needs so much information about the rules and regulations currently going on those matters.They just don’t need information they need the correct information.They can use some application that will collect the perfect information and store it in the database.The application can also parse the information for verification,it can be done through web.By the use of semantic web technology it can make information available to all publicly and privately.If information are transparent then the clients those who need to go to the financial institutions can get some idea before visiting those institutions.

I think if this type of application can be built then it will be very flexible for both the side clients and financial institutions.It also has better future impact.

 

Why Semantic Technology Will Have an Impact on Geographic Data July 1, 2011

Posted by davevankampen in Summer 2011 1st Session.
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    Critical Components of Semantic Technology

The critical components of semantic technology are all in the meta-data. The content is all already out there, on sites like Wikipedia and other large data sources, or sources of data mining. However, it is all mostly structured in human-readable ways. Semantic technology is about adding the information around the human information to make it portable and readable for machines. This is called meta-data, and it is what structures like RDF and OWL are based on. These frameworks are used to create a structure of relationships easily parsable and transferrable between machines, so they can communicate meaning without the need for human intervention.

    One application of Semantic Technology

One possible excellent application for Semantic Technology is geographic information. This is used by many different industries, including agriculture (farmers in fields), aviation (airplanes navigating around the world), military (tactical movements), and many others. There are tons of different groups collecting gigabytes of information about the world we are in, almost all of which would be useful to the other groups collecting very similar information. However, there is very little standardization (besides GPS data formats).

Due to this, I believe that this realm is prime for the incorporation of Semantic Technology. Much like the Ordnance Survey group (linked here) groups all over the world are collecting geographic information. If this was put in a central location that all groups could use, a redundancy of effort could be removed, and we could collectively develop a much more accurate and detailed picture of the world in which we all live.

There are, of course, barriers to this, and security concerns. Naturally, military operations would generally not be traced or saved, and some countries would not like much information about their geography shared. However, overall, I think this is a excellent use for Semantic Technology, and will definitely grow in the years to come.

Semantic Web and Google Maps July 1, 2011

Posted by 3561martinr in Summer 2011 1st Session.
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This post provides an explanation of the Semantic Web and a possible application of the technology. It begins with a brief description of the components of the Semantic Web and then follows with a description of how it might be applied to the Google Maps application.

 Semantic Web technology is an approach to create and link data sets together in a machine readable format throughout the web. To achieve this, the data is described using RDF to create data triples each consisting of a subject, predicate, and object. The data must also be classified into data hierarchies and other relationships using ontology standards such as OWL. From this point, the various triples are stored in databases called triplestores. Queries can then be written against one or more triples in the triplestores using SPARQL to produce result sets useful in building dynamic web pages. Rules of inference can also be used to generate additional relationships between linked data increasing the power and flexibility of the Semantic Web.

 An application I use often is Google Maps. Knowing that Google uses the Semantic Web and judging from the amount of additional information that often appears when I select a route, the Semantic Web is likely already being leveraged by Google Maps. For example, when I search between two points in Google Maps, I see a traffic icon which, when clicked, enables me to look at current traffic conditions, view photos, access webcams, or display labels associated with the chosen route. There is even a list of tags relevant to the area I could select for different topics which would pull in even more relevant data.

 Even with all of the Semantic Web capability that is probably being used, there is still much opportunity to incorporate more data. For example, when traveling less familiar routes, it could be helpful to not only see a route’s traffic conditions, but its safety conditions as well. Safety conditions could be based on current traffic or weather conditions or maybe the accident history of the route. In my neighborhood for example, there is a five mile stretch of road which claims one of the highest car to deer collision rates in the state, as reported by a local insurance agency, making it less safe. Another concern is that certain intersections have unusually high numbers of collisions. If this data was made available to the Semantic Web, it could be pulled in and labels could be placed along the route in high risk areas alerting drivers unfamiliar with the area. Furthermore, the application could generate not only the shortest or fastest route, but it could use this data to generate the statistically safest route given a variety of current conditions. I would definitely find this type of information beneficial and hope to see it incorporated in the future.

 

Why Semantic Web Technology Will Have a Major Impact on Stock Trading June 30, 2011

Posted by rzmuedu in Summer 2011 1st Session.
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The critical components of Semantic Web Technology includes data that are stored in the network and linked together, the model describing the data, and the query language that can be used to extract these data. In more detail, the data stored in the network must have been meaningfully described by a language such as RDF to construct a data model, which means forming the links between data. Some typical structure can be defined by using XML or Turtle. Other language such OWL extends the vocabulary for describing the data’s properties, relationships, equalities, etc. The data model can be accessed by query language for semantic web such as SPARQL to query the web data sources and displaying them in some formatted way defined by user.

Stocking trading is a complicated decision making process requiring tons of information to analyze. I think semantic web technology will have a positive impact on applications developed to assist stocking trading decision makings. Semantic web technology can be applied to extract data from the network more quickly and efficiently. The things to be extracted can be press release, news, important figures, even blog posts and twits related to a specific stock. Then an application can analyze these data by applying however sophisticated algorithms or theories to come up with a trend of the stock with a probability or something to help the security traders making a decision.

Why Semantic Web Technology Will Have a Major Impact on Electronic Commerce June 30, 2011

Posted by shuliuls in Summer 2011 1st Session.
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The semantic web comprises the standards and tools of XML, RDF, RDF Schema and OWL that are organized in the semantic web technology.

In my opinion, XML stands for eXtensible Markup Language and it’s a markup language much like HTML. XML was designed to transport and store data, not to display data. We need to define our own tags because XML tags are not predefined; RDF, which extends XML, defines a general common data model that adheres to web principles. RDF provides a consistent, standardized way of describing and querying Internet resources, from text pages and graphics to audio files and video clips. It gives syntactic interoperability, and provides the base layer for building a semantic web. RDF defines a directed graph of relationships; RDF schema allows a designer to define and publish the vocabulary used by an RDF data model. Both RDF and RDF-Schema are based on XML and XML-Schema. The existence of standards for describing data and data attributes enables the development of a set of readily available tools to read and exploit data from multiple sources; OWL is a Web Ontology language. It is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema by providing additional vocabulary along with a formal semantics.

The application I pick is electronic commerce and I think semantic web technology will have a major impact on electronic commerce. Bringing electronic commerce to its full potential requires a P2P approach. Anybody must be able to trade and negotiate with anybody else. However, such an open and flexible method for electronic commerce has to deal with many obstacles before it becomes a reality.

Mechanized support is needed in finding and comparing vendors and their offers. Currently, nearly all of this work is done manually which seriously hampers the scalability of electronic commerce. Semantic web technology can make it a different story: machine-processable semantics of information allow the mechanization of these tasks. In addition, mechanized support is needed in dealing with numerous and heterogeneous data formats. Various “standards” exist on how to describe products and services, product catalogues and business documents. Semantic web technology is required to define such standards better and to map between them. Efficient bridges between different terminologies are essential for openness and scalability.

Shu Liu

Why Semantic Web MAY have a major impact on ISR data mining June 30, 2011

Posted by 3562pittena in Summer 2011 1st Session.
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The Critical Components of Semantic Web Technology

In my opinion, the whole idea of the semantic web is the interconnection of data on the web. It about having a computer know how certain elements of data relate to other elements simply by marking them up that way. In order to do this, some of the components of the semantic web are RDF and OWL, then use SPARQL to query the data sources. RDF is a language used to model the data on the web page and OWL is used to express relationships between those models. The relationships made in OWL are much more complex than just a 1-to-1 relationship or other simple relationships. They can be one of many different relationships.

Possible Application of the Semantic Web

One application our business could potentially be working on is something called ISR (Intelligence, Surveillance and Reconnaissance). The idea is to send out a UAV (unmanned aerial vehicle) into a hostile territory, take surveillance images, then come back and report data to the “home base”. The problem they currently have is the pure amount of data that comes back from the UAV. They come back with RACKS of hard drives full of images taken from 10000-15000 ft. Now the “home base” must go through all the images withing 72 hours of the time the picture was taken otherwise the data becomes obsolete. Even then, data the is 24 hours old for a moving target is already too old. One can imaging that someone’s job in the Armed Forces could be to simply analyze data.

In order to simplify this process, what if we could take the data and simplify it so that the person analyzing the data only saw what they wanted to see. If we could pull out objects in the images (truck, person, car, building, etc) then relate that data together geographically (also using time as a scale…so a car in one place could be in a different place later in time, but it is the same car) then we could greatly reduce the amount of work the data analyzer does.

This seems like a “Big Data” problem but I could see the semantic web technology coming into play. There are many relationships that need to be made for all this data and if we could relate all the data automatically, then mine that data for relationships (like “truck near building X at time Y”) then the data analysis would take a significant less amount of time.

Critical Components of Semantic Web Technology June 30, 2011

Posted by zaffkea in Summer 2011 1st Session.
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Semantic web technology is all about organizing data and making it accessible. In this online seminar we have looked at a number of upcoming technologies that are emerging like OWL, SPARQL, triplestores, DBpedia, Protégé, etc. I think these technologies and others like them are really going to empower the average person by giving them access not only to more data, but to more accurate data and more specific data.

One application of the semantic web that I think would be really useful in the marketing industry is associating people’s purchasing preferences with their taste in music, clothing, etc. I realize that Amazon.com is already sort of doing this with their ‘people who bought this, also bought: ___’ feature, but I think the semantic web could really take it up a notch.

Let’s say you own a motorcycle dealership, and someone walks in and says they want to buy a motorcycle, but they can’t make up their mind. You could sit down with your confused customer with a semantic web app and input data about things they know they like already – foods, music, movies, etc. Then the app would return a picture of their ideal motorcycle based on their other preferences. You could even take it so far as to customize that motorcycle, for example, someone who likes one type of music might want a lot of chrome on his or her motorcycle, whereas someone who likes another type might want everything to be blacked out.

Semantic Technology and Crystal Reports June 30, 2011

Posted by kirbyr in Summer 2011 1st Session.
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What would a standard reporting tool look like using semantic technology?  In this post I will describe my thoughts on this topic.  I will base my model upon the Crystal Reports software, since I am familiar with that tool.

Like relational databases, semantic technology also involves a data source and a data model for how data interacts or relates to other data.  When using a semantic technology framework, instead of building a formal table structure to show the data relationships, information about data is encoded and stored along with the information.  There are no data tables, or data keys suggesting how information should be linked together.  The storage structure commonly used is called a triple, and the most commonly used language of implementation is called Resource Description Framework (RDF: http://www.w3.org/TR/2004/REC-rdf-primer-20040210/ ).  Within a triple, there are three pieces of information: a subject, predicate, and object.  Triples are used to encode and describe information.

In order to interpret the meaning of a triple, an ontology, or knowledge system needs to be defined for the described data.  An ontology maps out the connections for a data system, and is usually hierarchical.  For example, an ontology for mammals might denote that the class cat has subclasses of housecats, lions, and tigers.  The ontology might also provide attributes describing the cats, such as fur color or minimum and maximum weight.  The ontology provides the meaning for the data described by RDF triples.  When using the semantic web, ontologies are referred to by a URI (Universal Resource Indicator), and can be used to compare or translate one data set to another.

Another important component for semantic technology systems is a query tool.  A data set is not very useful without having a way to search through the data.  A common query tool used is SPARQL (http://www.w3.org/TR/rdf-sparql-query/).  The syntax used for SPARQL queries is similar to SQL queries used to search relational databases, with the exception that database tables are not specified since there are no tables defined for the dataset.

So where does Crystal Reports fit into this?  Crystal Reports is a reporting tool that interfaces with traditional relational databases as the information source for a report.  Reports are built by linking tables together using key data fields.  Each table is a collection of related information.  Table information is mapped out and designed in advance.  This method of reporting and interacting with data is very different from how semantic technology works.

One advantage of Crystal Reports is that the average user does not need to know how to write complex queries to be able to create reports.  Instead, the user employs a graphical interface to link tables together, extract information, and arrange the data into the desired output.  If the data source used is semantic instead of relational, the Crystal Reports user would need to know how to build SPARQL or similar queries to create reports.  Semantic data does not use the standard relational table layout, meaning the user would have no guide for how to link data together.  This would prove to be an obstacle for inexperienced report writers.

I have been thinking of a way to solve this issue.  One idea is to replicate the table structure of relational databases with the structure of the dataset’s ontology.  When importing a dataset into Crystal Reports, the ontological structure could also be downloaded, and used as a guide for linking together data to create a report.  The user could then use the structure of the ontology for report purposes.

Overall I would say that the Crystal Reports tool is not ready to harness the power of semantic technology.  More thought needs to be put into solving the problem of linking together data triples in a consistent and easy manner.  Also, greater adoption of semantic technology in datasets will aid in the development of semantic technology reporting tools.