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University Of Punjab Gujranwala Campus “Research Papers Summary” Submitted By: Fatima Azhar(BT15109) Maleeha Aftab(BT15113) Submitted To: Dr. Ghulam MustafaSummary 1:An ontology-based personalized target advertisement system on interactive TV Different modified services from audience, as well as embattled advertisement services is facing enlarge of order from TV like IPTV. Then we introduced and developed a sample of a modified objective advertisement system using OWL by defining ontology-based semantic relations in the middle of IPTV programs and advertisements. During the development of this system, we paying attention on improving the semantic interpretation talent. This can be done by semantic relations between heterogeneous stuffing like TV programs, advertisements, and shopping products. as well as, we improved the competence of recycle of the ontology by modeling the private ontology from the TV program ontology and the situation cluster ontology from the private ontology.

Summary 2: Lexical Graphs for Improved Contextual Ad Recommendation This paper is present a novel contextual ad recommendation structure based on the concept of lexical graphs. There are four types of graph-based ad recommendation and conducted an evaluation learn to evaluate the significance of the planned structure recommendations that is offered by the base and AAK models. For this purpose we pick best proves that the use of lexical graphs can be valuable to the duty of ad recommendation. There is a string of realistic issues that one would need to speak to prior to applying the planned structure in a actual surroundings and are so measured as opportunity labor. For this purpose earliest, the web document collection needed. lastly, the planned come near relies to a great extent on the use of NLP utensils.

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Summary 3: An ontology-based approach to Chinese semantic advertising On a theoretical stage to equal Chinese web pages and advertisements , we introduced an ontology-based draw near to Chinese semantic advertising. We introduced the semantic advertising sculpt and settle a Chinese ontology called Taobao Ontology in an routine style. To match Chinese web pages and advertisements two key algorithms are developed by view the theoretical similarities as well as the term similarities. One restraint is that the presentation of our skill depends on the fullness of the Taobao Ontology.Summary 4:Keyword Management System based on Ontology for Contextual Advertising In this paper we use methodology to pertain semantic web technologies. We introduced a relations of keywords By using an Apriori algorithm, made ontology from connected keywords and not compulsory the keyword additional room process. The suggested system show the efficiency of keyword annex. Based on OWL language we introduced the advantage of an ontology.

If the current system should be distorted completely the efficiency of this system will also be increased, some the method is too complex. So, the recommended system consistently used a part of the current system. We hope to improve the system if we add new models . Summary 5:Concept-based Biclustering for Internet Advertising When company buys some advertising terms which describe their certain requirements, it also includes the detail of their opponent company. Company provides context for advertisement but also wants to know affective markets from advertisers.

It can be done by biclustering that consists of two subsets firm and terms. To solve this tasks Formal Concept Analysis is used but dataset can be of exponential size in the worst case. A new concept-based biclustering method is purposed to avoid these issues.Summary 6: A Semantic Framework for Personalized Ad Recommendation based on Advanced Textual Analysis The exertion discuss in this paper has accessible confirmation that semantic knowledge in mixture with the use of arithmetical terminological data captured in lexical graphs can be useful to the suggestion of satisfied substance spoken by text. More it has established the competence of employing official semantics that imprison the fundamental material of user preferences to attain wealthier and more significant recommendation, even when little in order about the user is accessible. The methodology described allows for proposal of any kind of satisfied item for which there are textual data and for any area for which semantic knowledge is accessible.Summary 7: A New Perspective in Pervasive Advertising To manage the quantity and the pertinence of the advertisements PervADs used.

Similarly,it provides companies with a controlling advertising instrument competent of attainment latent patrons with a very high exactitude. We plan to set up the likelihood for users to spread PervADs to other users in immediacy and to study the bang of this form of community advertisement in the property situation. The description and the assessment also include in our investigate program of dissimilar business models for PervADs,like patenting potential.Summary 8: Concept-based Recommendations for Internet Advertisement With the use of typical means of computer linguistics we obtained consequences show that a part of dependencies in database for purchases of advertisement phrases may be detected routinely , This allows one to pick up recommendations and suggest good means of position, which is very significant for creation Top-N recommendations. one more benefit of the loom consists in the opportunity of detecting connected announcement phrases not given honestly in data.

Results of FCA-based biclusterization show the prospect of detecting comparatively huge announcement markets (with more than 20 participants) given by companies and advertising phrases. Ontologies like WordNet is used to improve the planned draw near.Summary 9: Sentiment-Oriented Contextual Advertising In this paper, we focus the sentiments of blog pages and se this information to display sentiment-oriented contextual advertising. For sentiment discovery, we compared machine learning-based algorithms with dissimilar quality sets and two linear models. The data source for training we used. Using learning algorithms our results showed .

primary, we compared SOCA with Google AdSense and establish that our future technique with response discovery can attain greater presentation. With the passage of time we mean to behavior a more complete psychiatry of our model and travel around the efficiency of response uncovering with dissimilar engine learning algorithms.Summary 10: Matching GitHub developer profiles to job advertisementsSummary This paper proposed a pipeline for the automated extraction of developer profiles for the purposes of matching them with job advertisements.

It uses the vector space model and the DBPedia Ontology. The vector space model provides a natural mechanism to determine the similarity between the devised job and developer profile vectors, namely the cosine of the angle between the two vectors (the so-called cosine similarity), which is bounded to a value in 0,1 where a larger score indicates higher similarity.Summary 11: Lexeme: An Ontology-Based Semantic Advertising Networks In this paper we accessible a example of a semantic publicity network. This provides ad and Web site satisfied match using semantic technology and ontology. The equal leadership is based on the ontology conceptualizing the marketable products in the education knowledge area. Based on the conducted experiments, the semantic publicity network shows an in general augment in the accuracy of the advertise-publisher content based match compared to keyword-match in the specific domain information. In add to in accuracy is a very vital direct line to calculate the success of an publicity movement since advertising to the right purchaser means expenditure fewer force, less time, and less money compare to pursue the wrong forecast and advertising to the wrong channel.Summary 12: Ontology-based personalized couple clustering for heterogeneous product recommendation in mobile marketing Mobile marketing has been more and more significant as this channel is a individual surroundings that will effect in elevated crash.

Recommender systems recommending goods on a conversation root in genuine time turn into one of the most vital everyday job in movable advertising. though, unpaid to the restriction of mobile phones the finest mode for customers to leave their welfare and preferences is during spoken announcement.


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