matching

Find minimum vertex Cover for bipartite graph given the maximum matching

由 做~自己de王妃 提交于 2019-12-09 13:51:13
问题 I seem to have found an algorithm but am having trouble understanding it, I was wondering if any of you knew the generic outline of the algorithm. Here is the link to the algorithm I found on page 2 http://www.cse.iitb.ac.in/~sundar/cs435/lecture23.pdf 回答1: Algorithm is simple as that: Find unmatched vertex, mark it as not included in minimum vertex cover. Mark all matched neighbours of this vertex as included in minimum vertex cover. Treat all mates of vertexes from previous step as

Matching fuzzy strings

由 只谈情不闲聊 提交于 2019-12-09 11:12:40
问题 I have two tables that I need to merge together in PostgreSQL, on the common variable "company name." Unfortunately many of the company names don't match exactly (i.e. MICROSOFT in one table, MICROSFT in the other). I've tried removing common words from both columns such as "corporation" or "inc" or "ltd" in order to try to standardize names across both tables, but I'm having trouble thinking of additional strategies. Any ideas? Thanks. Also, if necessary I can do this in R. 回答1: Have you

Android - Frame layout height not matching with coordinator layout

由 蓝咒 提交于 2019-12-09 09:15:38
问题 I have a problem with my FrameLayout (Container in Drawer Layout). The height of the FrameLayout exceeds the screen height (below the android default menu buttons at bottom). <android.support.design.widget.CoordinatorLayout android:id="@+id/main_content" android:layout_width="fill_parent" android:layout_height="fill_parent"> <android.support.design.widget.AppBarLayout android:id="@+id/navContainer" android:layout_width="match_parent" android:layout_height="wrap_content"> <android.support.v7

Bipartite Matching

由 给你一囗甜甜゛ 提交于 2019-12-09 04:24:27
How can I implement a bipartite matching algorithm (probably based on a max-flow algorithm) in C or C++ ? To be specific, I have this input in a file: (1,3) (1,5) (2,5) (M,F) --> where M represents id of MALE and F is id of FEMALE. I need to find the maximum number of matches and show matched couples. Like: matches: 1&3 , 2&5 I have read in some books I can base this problem on a "maximum flow in a network" algorithm, but I couldn't find any specific info other than the sentence "this problem can be solved by .... algorithm". I have little knowledge about max-flow, and dont know how to

match and add the cluster number to the original data

由 我与影子孤独终老i 提交于 2019-12-08 13:50:37
I am using the regular method to do a Hierarchical Clustering project. mydata.dtm <- TermDocumentMatrix(mydata.corpus) mydata.dtm2 <- removeSparseTerms(mydata.dtm, sparse=0.98) mydata.df <- as.data.frame(inspect(mydata.dtm2)) mydata.df.scale <- scale(mydata.df) d <- dist(mydata.df.scale, method = "euclidean") # distance matrix fit <- hclust(d, method="ward") groups <- cutree(fit, k=10) groups congestion cough ear eye fever flu fluzonenon medicare painpressure physical pink ppd pressure 1 2 3 4 5 6 5 5 5 7 4 8 5 rash screening shot sinus sore sports symptoms throat uti 5 5 6 1 9 7 5 9 10 And I

Best pattern Matching algorithm implemented in Java

由 陌路散爱 提交于 2019-12-08 11:48:46
问题 I am new to Java . My problem is I have to select the rows of an entire file (Size less than 70MB) to match my pattern (e.g. <subject> <Predicate> <Object> ). Currently I am using basic string matching algorithm bit it takes time so I want to use "Boyer-Moore algorithm". Is it good to use? Do we have some other better solution? If yes Please let me know and the code also in Java. 回答1: A quick Google returned: BoyerMoore implementation Boyer-Moore string search algorithm (Java) Maybe you

What is the optimal way to choose a set of features for excluding items based on a bitmask when matching against a large set?

由 旧巷老猫 提交于 2019-12-08 07:26:19
问题 Suppose I have a large, static set of objects, and I have an object that I want to match against all of them according to a complicated set of criteria that entails an expensive test. Suppose also that it's possible to identify a large set of features that can be used to exclude potential matches, thereby avoiding the expensive test. If a feature is present in the object I am testing, then I can exclude any objects in the set that don't have this feature. In other words, the presence of the

match and add the cluster number to the original data

由 半城伤御伤魂 提交于 2019-12-08 07:14:50
问题 I am using the regular method to do a Hierarchical Clustering project. mydata.dtm <- TermDocumentMatrix(mydata.corpus) mydata.dtm2 <- removeSparseTerms(mydata.dtm, sparse=0.98) mydata.df <- as.data.frame(inspect(mydata.dtm2)) mydata.df.scale <- scale(mydata.df) d <- dist(mydata.df.scale, method = "euclidean") # distance matrix fit <- hclust(d, method="ward") groups <- cutree(fit, k=10) groups congestion cough ear eye fever flu fluzonenon medicare painpressure physical pink ppd pressure 1 2 3

Grep file with two columns as input

由 爱⌒轻易说出口 提交于 2019-12-08 03:31:14
问题 I have a file containing lines like: "ALMEREWEG ";" 45 ";" ";"ZEEWOLDE ";"3891ZN" "ALMEREWEG ";" 50 ";" ";"ZEEWOLDE ";"3891ZP" "ALMEREWEG ";" 51 ";" ";"ZEEWOLDE ";"3891ZN" "ALMEREWEG ";" 52 ";" ";"ZEEWOLDE ";"3891ZP" "ALMEREWEG ";" 53 ";" ";"ZEEWOLDE ";"3891ZN" and I have a second file containing lines like: 3891ZP;50; 3891ZN;53;A 3891ZN;53;B 3891ZN;54; Now I want to grep the first file based on the pattern of the second file, where: A) the 1st column of the 2nd file is present in the 5th

Maximum weighted bipartite matching _with_ directed edges

由 非 Y 不嫁゛ 提交于 2019-12-08 02:46:59
问题 I know various algorithms to compute the maximum weighted matching of weighted, undirected bipartite graphs (i.e. the assignment problem): For instance ... The Hungarian Algorithm, Bellman-Ford or even the Blossom algorithm (which works for general, i.e. not bipartite, graphs). However, how can I compute the maximum weighted matching if the edges of the bipartite graph are weighted and directed ? I would appreciate pointers to algorithms with polinomial complexity or prior transformations to
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