حلالہ اور مروجہ حلالہ سنٹرز: ایک تجزیاتی مطالعہ

Almighty Allah made marriage a source of affection and love among the human beings. He also ordered to uphold this relation as much as possible. If, on one way or the other the relationship of a couple becomes so unpleasant that their family life becomes impossible to move any more further. In this case the Islamic “Sharia’h” recommends opening of the ways for their respectable separation in the shapes of “Divorce” and “Khula’a” (divorce obtained on wife’s initiative, s). Though Islamic sharia’h has declared “Divorce” as legal act, yet marriage being a great sacred relation which is desired to be retained intact to the maximum, it has been named as the most unpleasant among the permissible acts in Islam. Some human beings very abruptly break the same relation (Nikah) without proper consideration. Some of these persons later on repent on what they have done. Allah Almighty  therefore, very affectionately has allowed men after uttering two times the words, ‘Divorcee (Talaq) at different times to reconcile with their wives. But if he disrespecting this great relation stress-passes the final time and utters the word “Divorce” (Talaq) for the third time in his life so the religion has fixed certain punishment for his this very irresponsible act as a punishment that though, both spouses may agree to continue their married life, Islam does not allow them to do so, prior to undergoing the process of re-marrying  the woman with another person to fulfill the condition of her reunion with her first husband. This process is called “Halala”  In the article under reference side by side with presenting the literal meaning and idiomatic definitions of Halala, its Shari status has also been elaborated. Efforts  have been intensified to recollect the different views of all jurists  regarding this practice and examine the same analytically. In addition to that with the help of irrefutable proofs, the adverse effects of the so called “Halala, s centers” have been proved to warn the people to stay away from them.

Grand: Graph Based Author Name Disambiguation Framework

Author name disambiguation is a challenging research area in the field of biblio metric analysis, scientometrics, and informetrics. Author name ambiguity may occur in two ways, when multiple authors share a common name, or an author’s multiple name variations appear in the bibliographic databases, such as DBLP, ACM, and Google Scholar. In both these scenarios, it is difficult to be certain about the accuracy of the retrieved results. Proper identification of one’s work from other’s is necessary due to many reasons, for example, in author ranking sites such as the Arnetminer, presence of author’s name ambiguity in citations leads to wrong metrics such as h-index, g-index, and i-index. Author name am biguity is one of the main errors for the wrong analysis in these bibliographic databases. To improve the accuracy of aforementioned metrics, it is necessary to disambiguate these ambiguous authors. Similarly, these bibliographic databases provide content as an input to visual bibliographic information retrieval systems that are currently used for expert (supervisor) finding, specific literature searching, selecting reviewers, and detecting a potential conflict of interests. Existing author name disambiguation techniques require a representative labeled data set for the training of the model, or require a number of ambiguous authors known a priori, or require extra information from the Web, or need user feed back, and are less scalable due to the requirement of training thousands of models for each ambiguous author. In this dissertation, a complete author name dis ambiguation framework called “GRAND” is presented that consists of four main algorithms, one each for the resolution of homonyms, synonyms, sole authors, and incremental author’s name ambiguity. The first algorithm is DISC that exploits graph semantics, similarity measures, and community detection algorithms to disambiguate homonyms. The citation data set is preprocessed and ambiguous author blocks are created. DISC utilizes only two citation attributes–co-authors and titles, which are implicit bibliographic information in all bibliographic databases. The co-author’s graph of the citation data set is constructed and “GSkeletonClu: A graph Structural Clustering Algo rithm for networks” is used to identify hub vertices, outliers, and clusters of nodes in the co-author’s graph. Homonyms are resolved by splitting these clusters of nodes across the hub nodes if the similarity between their title feature vectors is less than a threshold. The second algorithm is SISTER that uses graph-based se mantic similarity measure “SynGeo”. It preprocesses and constructs co-author’s graph of the citation’s data set. Synonyms are resolved by exploiting SynGeo, which is based on syntactic similarity and graph geodesics between compared nodes. The third algorithm is GCLUSIM, which detects and disambiguates sole authors. In GCLUSIM, sole author’s and disambiguated author’s title feature vectors are constructed to find the similarity between them. On the basis of this similarity, a sole author may be merged with the disambiguated clusters. As our final contribution, the fourth algorithm is CAND that exploits author name in dices, author profiles, and a comparison function to solve the incremental author’s name ambiguity. Author name indices enhance the overall system performance and author profile models help in disambiguation of the incremental insertions. The comparison function utilizes the most strong bibliometric features–co-author, titles, and self-citations. The proposed algorithms are effective than state of the art methods in terms of clustering metrics. Furthermore, we believe that our pro posed algorithms in this dissertation can serve a baseline for future author name disambiguation studies.